JP6903458B2 - Impression amount estimation method, impression amount estimation device, and building design method - Google Patents

Description

The present invention relates to an impression quantity estimation method, an impression quantity estimation device, and a building design method.

In evaluating the environment of an indoor space, it is important to understand the brightness and impression that a person feels about the indoor space. The illuminance standard of the Japanese Industrial Standards is often used for the lighting design of the indoor space.
Further, in recent years, the importance of brightness has increased in the evaluation of the light environment, and a spatial evaluation method based on brightness has been proposed.
Although methods have been proposed that more accurately predict the "brightness" that people feel and utilize it in design, space design based on illuminance is still often performed due to the ease of handling illuminance, and It depends largely on the experience and sense of the designer.

Regarding the technology for evaluating the brightness environment of the space, the statistics of the brightness distribution and the distribution situation within the 180-degree circle in the front field of view were obtained from the input image data, and the indoor space of the different brightness environment was evaluated in advance by the observer. There is known a technique of predicting a feeling of brightness by a brightness feeling prediction formula derived from evaluation data and evaluating using the prediction result (see, for example, Patent Document 1).

Japanese Unexamined Patent Publication No. 2004-354200

However, since the feeling of brightness of the indoor space is calculated as the average value of the space of interest, it is difficult to apply it to the design inside the indoor space. In addition, when designing an interior space based on the experience and sense of an interior advisor, the result of designing the interior space may differ depending on the interior advisor.

The present invention has been made in view of the above-mentioned problems, and is an impression amount estimation method capable of easily estimating the impression amount of the indoor space even when the design is changed for each part constituting the indoor space. An object of the present invention is to provide an impression amount estimation device and a building design method.

(1) To solve the above problems, an embodiment of the present invention, a computer device, a striking amount estimation method for estimating the impression amount for the room to be recognized from a particular viewpoint, the computer device, the room A step of acquiring input information including lighting information and daylight information, a step of the computer device generating a brightness image based on the input information, and a step of the computer device producing the brightness image in the room. Based on the step of dividing each part of the room into information for each part of the room entering the specific viewpoint, and the computer device weighting the information for each part of the room and the information for each part of the room. It is an impression amount estimation method including a step of calculating a value indicating an impression amount.

According to the impression amount estimation method according to the present embodiment, input information including room lighting information and daylight information is acquired, a brightness image is generated based on the acquired input information, and the generated brightness image is generated. Divide into information for each part of the room that enters a specific viewpoint from each part of the room. Then, a value indicating the impression amount is calculated based on the information for each part of the room and the weighting for the information for each part of the room.
In this way, the brightness image generated based on the input information is divided into information for each part of the room that enters a specific viewpoint from each part of the room. Since the degree of can be easily grasped, it can be applied to space design.
Then, a value indicating the impression amount can be calculated based on the information for each part of the room and the weighting for the information for each part of the room. That is, the subjective impression amount felt by a person can be estimated from the physical quantity such as the luminance information. Compared to the case where the feeling of brightness of the indoor space is calculated as the average value of the space of interest, it is possible to select the material, color, window, etc. for each constituent surface, so it is possible to design the space. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each constituent surface constituting the indoor space. Since the user can grasp the value indicating the quantified impression amount, the impression amount can be evaluated at a certain level regardless of the experience and sense of the interior advisor.

(2) In one embodiment of the present invention, in the above-mentioned impression amount estimation method, in the step of dividing, the computer device inputs the brightness image from the ceiling of the room to the specific viewpoint, and the ceiling information. The calculation is divided into wall information entering the specific viewpoint from the wall of the room, floor information entering the specific viewpoint from the floor of the room, and window information entering the specific viewpoint from the window of the room. In the step, the computer device performs weighting on the ceiling information and the ceiling information, weighting on the wall information and the wall information, weighting on the floor information and the floor information, and the window information and the window information. A value indicating the impression amount may be calculated based on the weighting.

By configuring in this way, the generated brightness image is divided into ceiling information that enters a specific viewpoint from the ceiling of the room, wall information that enters a specific viewpoint from the wall of the room, and floor that enters a specific viewpoint from the floor of the room. It can be divided into information and window information that enters a specific viewpoint from the window of the room. Then, a value indicating an impression amount based on the weighting of the ceiling information and the ceiling information, the weighting of the wall information and the wall information, the weighting of the floor information and the floor information, and the weighting of the window information and the window information. Can be calculated.
In this way, the brightness image generated based on the input information enters a specific viewpoint from the ceiling of the room, wall information entering a specific viewpoint from the wall of the room, and entering a specific viewpoint from the floor of the room. Since it is divided into floor information and window information that enters the specific viewpoint from the window of the room, it is possible to easily grasp the degree of brightness in daily life for each constituent surface such as the ceiling, wall, floor, and window. , Can be applied to space design.
Then, a value indicating an impression amount based on the weighting of the ceiling information and the ceiling information, the weighting of the wall information and the wall information, the weighting of the floor information and the floor information, and the weighting of the window information and the window information. Can be calculated. That is, the subjective impression amount felt by a person can be estimated from the physical quantity such as the luminance information. Compared to the case where the feeling of brightness of the indoor space is calculated as the average value of the space of interest, it is possible to select the material, color, window, etc. for each constituent surface, so it is possible to design the space. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each constituent surface constituting the indoor space. Since the user can grasp the value indicating the quantified impression amount, the impression amount can be evaluated at a certain level regardless of the experience and sense of the interior advisor.

(3) In one embodiment of the present invention, in the above-mentioned impression amount estimation method, the computer device has a step of generating a brightness image from the brightness image generated in the step of generating the brightness image. In the dividing step, the computer device may divide the brightness image into information for each part of the room that enters a specific viewpoint from each part of the room.

With this configuration, the brightness image generated from the brightness image can be divided into information for each part of the room that enters the specific viewpoint from each part of the room.
In this way, since the brightness image generated from the brightness image is divided into information for each part of the room that enters the specific viewpoint from each part of the room, design is performed for each constituent surface such as each part of the room. be able to.

(4) In one embodiment of the present invention, in the above-mentioned impression amount estimation method, in the division step, the computer device and the ceiling information that the brightness image enters the specific viewpoint from the ceiling of the room. , The wall information entering the specific viewpoint from the wall of the room, the floor information entering the specific viewpoint from the floor of the room, and the window information entering the specific viewpoint from the window of the room are divided into the above. In the step of calculating, the computer device performs weighting on the ceiling information and the ceiling information, weighting on the wall information and the wall information, weighting on the floor information and the floor information, and window information and the window information. A value indicating the amount of impression may be calculated based on the weighting with respect to.

By configuring in this way, the brightness image generated from the brightness image can be displayed as ceiling information that enters a specific viewpoint from the ceiling of the room, wall information that enters a specific viewpoint from the wall of the room, and specific from the floor of the room. It can be divided into floor information that enters the viewpoint and window information that enters a specific viewpoint from the window of the room.
In this way, the brightness image generated from the brightness image enters the ceiling information from the ceiling of the room to a specific viewpoint, the wall information from the wall of the room to the specific viewpoint, and the floor from the floor of the room to the specific viewpoint. Since the information is divided into the information and the window information that enters the specific viewpoint from the window of the room, the design can be performed for each constituent surface such as the ceiling, the wall, the floor, and the window.

(5) In one embodiment of the present invention, in the impression amount estimation method described above, in the calculation step, the computer device performs the geometric mean of the ceiling information, the geometric mean of the wall information, and the geometric mean of the floor information. , And the geometric mean of the window information, and further based on the geometric mean of the ceiling information, the geometric mean of the wall information, the geometric mean of the floor information, and the geometric mean of the window information. Good.

With this configuration, the geometric mean of ceiling information, the geometric mean of wall information, the geometric mean of floor information, and the geometric mean of window information are calculated, and the geometric mean of ceiling information, the geometric mean of wall information, and the floor information Based on the geometric mean of the above and the geometric mean of the window information, a value indicating the impression amount can be calculated, and the impression amount for the room can be estimated based on the value indicating the impression amount obtained by the calculation. That is, the subjective impression amount felt by a person can be estimated from the physical quantity such as the luminance information. Compared to the case where the feeling of brightness of the indoor space is calculated as the average value of the space of interest, it is possible to select the material, color, window, etc. for each constituent surface, so it is possible to design the space. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each constituent surface constituting the indoor space.

(6) In one embodiment of the present invention, in the above-mentioned impression amount estimation method, the computer device has a step of generating a glare image from the luminance image generated in the step of generating the luminance image. In the dividing step, the glare image may be divided into information for each part of the room that enters the specific viewpoint from each part of the room.

With this configuration, the glare image generated from the luminance image can be divided into information for each part of the room that enters the specific viewpoint from each part of the room.
In this way, the glare image generated from the luminance image is divided into information for each part of the room that enters the specific viewpoint from each part of the room, so design is performed for each constituent surface such as each part of the room. Can be done.

(7) In one embodiment of the present invention, in the above-mentioned impression amount estimation method, in the step of dividing, the computer device receives the glare image from the ceiling of the room into the specific viewpoint. It may be divided into wall information entering the specific viewpoint from the wall of the room, floor information entering the specific viewpoint from the floor of the room, and window information entering the specific viewpoint from the window of the room. Good.

By configuring in this way, the glare image generated from the brightness image is divided into ceiling information that enters a specific viewpoint from the ceiling of the room, wall information that enters a specific viewpoint from the wall of the room, and a specific viewpoint from the floor of the room. It can be divided into floor information that enters and window information that enters a specific viewpoint from the window of the room.
In this way, the glare image generated from the brightness image enters the specific viewpoint from the ceiling of the room, the wall information that enters the specific viewpoint from the wall of the room, and the floor information that enters the specific viewpoint from the floor of the room. And the window information that enters the specific viewpoint from the window of the room, so that the design can be performed for each constituent surface such as the ceiling, the wall, the floor, and the window.

(8) In one embodiment of the present invention, in the above-mentioned impression amount estimation method, in the step of calculating, the computer device performs the maximum value of the ceiling information, the maximum value of the wall information, and the maximum value of the floor information. , And a value indicating the amount of impression based on the maximum value of the window information, the maximum value of the ceiling information, the maximum value of the wall information, the maximum value of the floor information, and the maximum value of the window information. May be calculated.
By configuring in this way, the maximum value of ceiling information, the maximum value of wall information, the maximum value of floor information, and the maximum value of window information are calculated, and the maximum value of ceiling information, the maximum value of wall information, and floor information are calculated. Based on the maximum value of and the maximum value of the window information, a value indicating the impression amount can be calculated. That is, the subjective impression amount felt by a person can be estimated from the physical quantity such as the luminance information. Since the discomfort caused by the glare of the indoor space can be evaluated for each constituent surface, it is possible to easily determine whether glare is a problem in terms of the line of sight, which makes it easy to apply to space design and indoors. Even when the design is changed for each constituent surface that constitutes the space, the impression amount of the indoor space can be easily estimated.

(9) One embodiment of the present invention is an impression amount estimation device that estimates an impression amount for a room recognized from a specific viewpoint, and acquires input information including room lighting information and daylight information. A unit, a generation unit that generates a brightness image based on the input information, a division unit that divides the brightness image into information for each part of the room that enters a specific viewpoint from each part of the room, and the above. It is an impression amount estimation device including a calculation unit for calculating a value indicating an impression amount based on the information for each part of the room and the weighting for the information for each part of the room.
According to the impression amount estimation device according to the embodiment of the present invention, the invention is substantially the same except for the impression amount estimation method and the category, and the same actions and effects are exhibited.

(10) One embodiment of the present invention is a building design method executed by a computer device having the impression amount estimation method according to any one of the above (1) to (8).
According to the building design method according to the embodiment of the present invention, the invention is substantially the same invention except that the category is different from the impression amount estimation method, and the same action and effect are exhibited.

According to the present invention, the luminance image generated based on the input information is divided into the information for each part of the room that enters a specific viewpoint from each part of the room. Since the degree of brightness in the above can be easily grasped, it can be applied to space design.
Further, according to the present invention, a value indicating an impression amount is calculated based on the information for each part of the room and the weighting for the information for each part of the room, and the impression amount obtained by the calculation is shown. The amount of impression on the room can be estimated based on the value. That is, the subjective impression amount felt by a person can be estimated from the physical quantity such as the luminance information. Compared to the case where the feeling of brightness of the indoor space is calculated as the average value of the space of interest, it is possible to select the material, color, window, etc. for each constituent surface, so it is possible to design the space. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each constituent surface constituting the indoor space. Since the user can grasp the value indicating the quantified impression amount, the impression amount can be evaluated at a certain level regardless of the experience and sense of the interior advisor.

It is a figure which shows an example of the structure of an indoor space. It is a figure which shows an example of the hardware composition of the impression amount estimation apparatus 100 which concerns on embodiment. It is a functional block diagram of the impression amount estimation device which concerns on embodiment. It is a figure which shows an example of the input screen of the room space information. It is a figure which shows the display example of the luminance image. It is a flowchart which shows an example of the operation of the impression amount estimation apparatus which concerns on embodiment. It is a figure which shows the outline of the space where a simulation is performed. It is a figure which shows another example of an indoor space. It is a figure which shows another example of the composition of the interior space of a building. It is a functional block diagram of the impression amount estimation device which concerns on a modification. It is a flowchart which shows an example of the operation of the impression amount estimation apparatus which concerns on a modification. It is a figure which shows an example of the structure of an indoor space.

Next, a mode for carrying out the present invention will be described with reference to the drawings. The embodiments described below are merely examples, and the embodiments to which the present invention is applied are not limited to the following embodiments.
In all the drawings for explaining the embodiment, the same reference numerals are used for those having the same function, and the repeated description will be omitted.

(Impression amount estimation device)
The impression amount estimation device 100 according to the embodiment of the present invention is a computer device that evaluates the impression amount of the indoor space of the building. Specifically, the impression amount estimation device 100 acquires input information including room information (hereinafter, referred to as “indoor space information”) representing an indoor space indicating the shape and interior physical characteristics of the room, and uses the acquired indoor space information as the input information. Based on this, a luminance image is generated. The impression amount estimation device 100 divides the generated luminance image into each part of the room, and calculates information for each part of the room that enters a specific viewpoint from each part. Here, the part of the room means a part of the room that occupies a certain position. Then, the impression amount estimation device 100 calculates a value indicating the impression amount of the room based on each of the information for each part and the weighting for each of the information for each part. The impression amount estimation device 100 outputs the estimation result of the impression amount for the room based on the value indicating the obtained impression amount by the calculation.

Hereinafter, as an example, the case where the constituent surfaces of the room such as the ceiling, the wall, the floor, and the window are applied to each part of the room will be described. In this case, the impression amount estimation device 100 divides the generated luminance image into constituent surfaces such as a ceiling, a wall, a floor, and a window, and calculates information that enters a specific viewpoint from each constituent surface. Here, the specific viewpoint means a representative viewpoint of the assumed resident. Specifically, the posture of the resident can be considered to be standing, sitting, floor, etc., and the specific viewpoint can be the viewpoint of various positions in the height direction and the width direction of the room. For example, the impression amount estimation device 100 sets the viewpoint position according to the purpose of the room. Specifically, in the case of a basic standing space such as a kitchen, the impression amount estimation device 100 sets the viewpoint position to a height of about 1500 mm (the height of a woman's eyes) in front of the sink, and makes a living room. In the case of, the viewpoint position is set to 900 mm (floor seat) or 1200 mm (sofa seat) from the edge of the wall. Further, when evaluating as a basic space, the impression amount estimation device 100 is set with a height of about 1200 mm to 1500 mm as a representative in the center of the room.

Hereinafter, information entering a specific viewpoint from the ceiling of a room is referred to as "ceiling information", information entering a specific viewpoint from the wall of the room is referred to as "wall information", and information entering a specific viewpoint from the floor of the room is referred to as "information entering a specific viewpoint". It is called "floor information", and information that enters a specific viewpoint through a window is called "window information". Then, the impression amount estimation device 100 indicates the impression amount of the room based on each of the ceiling information, the wall information, the floor information and the window information, and the weighting for each of the ceiling information, the wall information, the floor information and the window information. Calculate the value. The impression amount estimation device 100 outputs the estimation result of the impression amount for the room based on the value indicating the obtained impression amount by the calculation. In addition, the amount of impression includes a feeling of openness, a feeling of coziness, likes and dislikes, glare, calmness, brightness, cheerfulness, comfort, liveliness, warmth, and the like.

(Composition of indoor space)
FIG. 1 is a diagram showing an example of the configuration of the interior space of a building. An example of the shape of the interior space is a quadrangular prism, and FIG. 1 shows the inside thereof. In FIG. 1, 20 indicates a viewpoint. Here, as an example, an indoor space recognized when the direction of the back side of the paper surface is viewed from the viewpoint 20 on the front side of the paper surface will be described. When viewed from the front side of the paper, the direction of the back of the paper is north.
The interior space includes a ceiling 1, a left side wall 2, a right side wall 3, a front wall 4, a floor 5, a window 11, and a lighting 13. The left side wall 2 is a wall that can be seen on the left side when the direction toward the back side of the paper surface is viewed from the viewpoint 20 on the front side of the paper surface. The right side wall 3 is a wall that can be seen on the right side when the direction toward the back side of the paper surface is viewed from the viewpoint 20 on the front side of the paper surface. The front wall 4 is a wall that can be seen in the front when the direction toward the back side of the paper surface is viewed from the viewpoint 20 on the front side of the paper surface. The window 11 is a window attached to the right side wall 3.
Input information including the indoor space identification information for identifying the indoor space and the indoor space information shown in FIG. 1 is input to the impression amount estimation device 100. Hereinafter, the impression amount estimation device 100 will be described.

(Configuration of impression amount estimation device)
FIG. 2 is a diagram showing an example of the hardware configuration of the impression amount estimation device 100 according to the embodiment. The impression amount estimation device 100 includes a CPU (Central Processing Unit) 102, a ROM (Read Only Memory) 104, a RAM (Random Access Memory) 106, an input / output device 108, a communication module 110, an auxiliary storage device 112, and a bus 120. ing.

The CPU 102 reads a program or the like for controlling the operation of the impression amount estimation device 100 from the ROM 104 or the auxiliary storage device 112, expands the program into the RAM 106, and executes the program.
The input / output device 108 displays an input screen for indoor space information, an evaluation result of the impression amount of the room, and the like. Further, the input / output device 108 accepts the user's operation. The input / output device 108 includes a touch panel, a pointing device, a touch pad, a display, and the like.
The communication module 110 is composed of an NFC module, a wireless LAN module, and the like. Further, the communication module 110 may be configured by USB (Universal Serial Bus). The communication module 110 communicates with an external device by NFC, wireless LAN, or wire.
The auxiliary storage device 112 is composed of a flash memory, an HDD (Hard Disk Drive), an SSD (Solid State Drive), an SD (Secure Digital) card, and the like. The auxiliary storage device 112 stores a program executed by the CPU 102.

(Functional configuration of impression amount estimation device)
FIG. 3 is a functional block diagram of the impression amount estimation device according to the embodiment.
The impression amount estimation device 100 includes the acquisition unit 152, the image generation unit 154, the division unit 156, the calculation unit 158, and the impression amount estimation unit 160 by executing the program developed on the RAM 106 from the auxiliary storage device 112 by the CPU 102. It functions as a storage unit 162 and an output unit 164.

(Each functional configuration of the impression amount estimation device)
Each functional configuration of the impression amount estimation device 100 will be described in detail with reference to FIGS. 2 and 3. In the following description of each function of the impression amount estimation device 100, the relationship with the main hardware for realizing each functional block of the impression amount estimation device 100 shown in FIG. 3 will also be described.
The acquisition unit 152 is realized by a command from the CPU 102 and an input / output device 108. The acquisition unit 152 acquires the input information input by the user from the input / output device 108. The input information includes indoor space identification information and indoor space information. The indoor space identification information is information for uniquely identifying the indoor space when there are a plurality of indoor spaces, and is represented by characters, symbols, and the like. The indoor space information includes output information of a light source such as lighting installed in a room and lighting information such as information on light distribution. In addition, the indoor space information includes daylight information which is information indicating the light shining through the window installed in the room. Daylight information is obtained based on the area where the room is installed, the date and time, the orientation, and the like.
When the impression amount estimation device 100 is activated, a screen for inputting indoor space identification information to the input / output device 108 is displayed. When the user inputs the indoor space identification information of the indoor space for which the impression amount is estimated on the screen for inputting the indoor space identification information, the indoor space information input screen is displayed.

FIG. 4 is a diagram showing an example of an input screen for indoor space information. The input screen 170 includes information indicating the size of the room such as width 202, depth 204, and ceiling height 206 as indoor space information. Here, the width 202 is the length in the horizontal direction between the left side wall 2 and the right side wall 3 included in the constituent surface of the indoor space. Depth 204 is the horizontal length between the viewpoint 20 and the front wall 4. The ceiling height 206 is the length of a perpendicular line extending from the ceiling 1 to the floor 5.
Further, the indoor space information includes window information such as window type 208, window arrangement 210, and number of windows 212. The window type 208 indicates a window type such as a sweep window, a high-waisted window, a high window, a ground window, and a full-height vertical window. The window arrangement 210 indicates the direction in which the windows are arranged, such as north, south, east, and west. The number of windows 212 indicates the number of windows included in the indoor space. Further, the indoor space information includes the window glass type 214 and the presence / absence of window hanging 216. The window glass type 214 indicates a type of window glass such as transparent glass and haze glass. The window hanging shows a lace curtain or the like.

Further, the interior space information includes material information indicating materials such as wall color 218, floor color 220, and ceiling color 222. The wall color 218 indicates the color of the left side wall 2, the color of the right side wall 3, and the color of the front wall 4.
In addition to the information shown in FIG. 4, the indoor space information includes lighting information such as the type, output, position, number, and light distribution pattern of the lighting fixture. The types of lighting fixtures indicate 13 types of lighting such as downlights and spotlights. The output indicates the total luminous flux output from the illumination 13. The position indicates the position where the illumination 13 is attached. The number indicates the number of lights 13 included in the indoor space. The light distribution pattern shows the spread of light from the illumination 13 such as general diffused light distribution, direct light distribution, semi-direct light distribution, semi-indirect light distribution, and indirect light distribution.
Further, the indoor space information includes room installation information such as the area where the room is installed and the orientation of the room.

The input information may include information other than the indoor space identification information and the indoor space information. For example, the input information may include date and time information for estimating the impression amount.
When the acquisition unit 152 acquires the indoor space identification information, the indoor space information, and the date and time information, the acquisition unit 152 outputs the acquired indoor space identification information, the indoor space information, and the date and time information to the image generation unit 154.
Further, the indoor space information input screen includes an evaluation value display button 224. The evaluation value display button 224 is a button pressed when displaying the estimation result of the impression amount on the input / output device 108.

The image generation unit 154 is realized by a command from the CPU 102. When the image generation unit 154 acquires the indoor space identification information, the indoor space information, and the date and time information from the acquisition unit 152, the image generation unit 154 uses the acquired indoor space information and the date and time information to display the room at the date and time included in the date and time information. A brightness image LI showing an image showing brightness is generated on the ceiling 1, the left side wall 2, the right side wall 3, the front wall 4, the floor 5, and the window 11. Luminance is a unit solid angle and luminous intensity per unit area, and brightness has three-dimensional information. Specifically, the image generation unit 154 generates a luminance image LI by using a radiosity method, a ray tracing method, or the like. By using the radiosity method, the final rendering result becomes closer to reality because it imitates the behavior of light that is close to the real world. By using the ray tracing method, a ray that reaches a certain point is traced in the opposite direction to draw an image or the like at that point. For example, in the case of a ray, the reflectance, transparency, and refractive index of the surface of the object. An image that reflects such things in detail can be obtained. Therefore, by using the ray tracing method, the path of the light beam is calculated pixel by pixel, so that high image quality can be drawn. The image generation unit 154 outputs the image information of the generated luminance image LI to the division unit 156.

The division unit 156 is realized by a command from the CPU 102. The division unit 156 acquires the image information of the luminance image LI from the image generation unit 154. By performing image processing on the acquired luminance image LI, the dividing portion 156 includes a ceiling 1, a left side wall 2, a right side wall 3, a front wall 4, a floor 5, and a window 11. Divide into. That is, the division unit 156 acquires the ceiling luminance image 1a that enters a specific viewpoint from the ceiling of the room by dividing the luminance image LI into the portion of the ceiling 1. Further, the division unit 156 acquires the left side wall brightness image 2a entering a specific viewpoint from the left side wall 2 of the room by dividing the brightness image LI into the left side wall 2. Further, the division unit 156 acquires the right side wall brightness image 3a entering a specific viewpoint from the right side wall 3 of the room by dividing the brightness image LI into the right side wall 3. Further, the dividing unit 156 acquires the front wall luminance image 4a entering a specific viewpoint from the front wall 4 of the room by dividing the luminance image LI into the portions of the front wall 4. Further, the division unit 156 acquires the floor brightness image 5a entering a specific viewpoint from the floor 5 of the room by dividing the brightness image LI into the floor 5. Further, the dividing unit 156 acquires the window luminance image 11a entering a specific viewpoint from the window 11 of the room by dividing the luminance image LI into the portion of the window 11.

FIG. 5 is a diagram showing a display example of the luminance image LI. FIG. 5 shows a ceiling brightness image 1a, a left side wall brightness image 2a, a right side wall brightness image 3a, a front wall brightness image 4a, a floor brightness image, 5a, and a window brightness image 11a included in the brightness image LI. .. In FIG. 5, the details of the image showing the brightness itself are omitted. Further, FIG. 5 shows a pixel 300, which is a minimum unit of color information to be displayed on the screen of an input / output device 108 such as a display device.
The division unit 156 includes image information of the ceiling brightness image 1a, image information of the left side wall brightness image 2a, image information of the right side wall brightness image 3a, image information of the front wall brightness image 4a, image information of the floor brightness image 5a, and window brightness. The image 11a and the image 11a are output to the calculation unit 158.
The calculation unit 158 is realized by an instruction from the CPU 102. The calculation unit 158 outputs the image information of the ceiling brightness image 1a, the image information of the left side wall brightness image 2a, the image information of the right side wall brightness image 3a, the image information of the front wall brightness image 4a, and the floor brightness image output by the division unit 156. The image information of 5a and the window brightness image 11a are acquired. The calculation unit 158 calculates the number of pixels included in each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a. The calculation unit 158 calculates the calculation result of the number of pixels included in each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a. Associate with indoor space identification information.

Further, the calculation unit 158 is included in each brightness image for each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a. The brightness (logarithmic value) of each pixel is read, and the geometric average of the read brightness is calculated. Here, the geometric mean is obtained by taking the root of the product of the read luminances (nth root if the number is n). The calculation unit 158 calculates the geometric mean of the brightness obtained from the ceiling brightness image 1a, the geometric mean of the brightness obtained from the left side wall brightness image 2a, and the brightness obtained from the right side wall brightness image 3a. The geometric mean calculation result of the above, the geometric mean calculation result of the brightness obtained from the front wall brightness image 4a, the geometric mean calculation result of the brightness obtained from the floor brightness image 5a, and the window brightness image 11a. The calculation result of the geometric mean of the brightness is associated with the indoor space identification information.
Hereinafter, the calculation result of the geometric average of the brightness obtained from the ceiling brightness image 1a is obtained from the ceiling brightness information, and the calculation result of the geometric average of the brightness obtained from the left side wall brightness image 2a is obtained from the left side wall brightness information and the right side wall brightness image 3a. The calculation result of the geometric average of the obtained brightness is the right side wall brightness information, the calculation result of the geometric average of the brightness obtained from the front wall brightness image 4a is the front wall brightness information, and the geometric average of the brightness obtained from the floor brightness image 5a. The calculation result of is called the floor brightness information, and the calculation result of the geometric average of the brightness obtained from the window brightness image 11a is called the window brightness information.

The calculation unit 158 totals the calculation results of the number of pixels included in each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a. To do. Hereinafter, the result of totaling the calculation results of the number of pixels included in each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a is calculated. , The number of pixels in the entire image.
The calculation unit 158 obtains the pixel ratio of the ceiling luminance image 1a to all the images by dividing the number of pixels included in the ceiling luminance image 1a by the number of pixels of all the images. Hereinafter, the pixel ratio of the ceiling brightness image 1a to all the images is referred to as a ceiling pixel ratio.
Further, the calculation unit 158 obtains the pixel ratio of the left side wall luminance image 2a to all the images by dividing the number of pixels included in the left side wall luminance image 2a by the number of pixels of all the images. Hereinafter, the pixel ratio of the left side wall brightness image 2a to all the images is referred to as the left side wall pixel ratio.

Further, the calculation unit 158 obtains the pixel ratio of the right side wall brightness image 3a to all the images by dividing the number of pixels included in the right side wall brightness image 3a by the number of pixels of the total image. Hereinafter, the pixel ratio of the right side wall brightness image 3a to all the images is referred to as the right side wall pixel ratio.
Further, the calculation unit 158 obtains the pixel ratio of the front wall luminance image 4a to all the images by dividing the number of pixels included in the front wall luminance image 4a by the number of pixels of all the images. Hereinafter, the pixel ratio of the front wall brightness image 4a to all the images is referred to as the front wall pixel ratio.
Further, the calculation unit 158 obtains the pixel ratio of the floor luminance image 5a to all the images by dividing the number of pixels included in the floor luminance image 5a by the number of pixels of all the images. Hereinafter, the pixel ratio of the floor brightness image 5a to all the images is referred to as a floor pixel ratio.
Further, the calculation unit 158 obtains the pixel ratio of the window luminance image 11a to all the images by dividing the number of pixels included in the window luminance image 11a by the number of pixels of all the images. Hereinafter, the pixel ratio of the window brightness image 11a to all the images is referred to as a window pixel ratio.

The calculation unit 158 includes the obtained ceiling pixel ratio, left side wall pixel ratio, right side wall pixel ratio, front wall pixel ratio, floor pixel ratio, and window pixel ratio, and ceiling brightness information, left side wall brightness information, and right side wall brightness information. By substituting the front wall brightness information, the floor brightness information, and the window brightness information into the estimation formula of the impression amount stored in the storage unit 162, the value indicating the impression amount is calculated. Specifically, the estimation formula of the impression amount is expressed by the formula (1). The derivation of the impression amount estimation formula will be described later.

Impression amount estimate = A + B (ceiling brightness information x ceiling pixel ratio) + C (left side wall brightness information x left side wall pixel ratio) + D (right side wall brightness information x right side wall pixel ratio) + E (front wall brightness information x front wall pixel) Ratio) + F (floor brightness information x floor pixel ratio) + G (window brightness information x window pixel ratio) (1)

In the formula (1), A, B, C, D, E, F, and G are real numbers and are preset by the administrator of the impression amount estimation device 100. A is a constant, B is a weighting for the ceiling brightness information, C is a weighting for the left side wall brightness information, D is a weighting for the right side wall brightness information, E is a weighting for the front wall brightness information, and F. Is a weighting for the floor luminance information, and G is a weighting for the window luminance information.
The estimated impressions of A, B, C, D, E, F, and G are openness, comfort, likes and dislikes, glare, calmness, brightness, cheerfulness, comfort, liveliness, or warmth. It takes a different value depending on whether it is.

The calculation unit 158 outputs a value indicating the impression amount to the impression amount estimation unit 160.
The impression amount estimation unit 160 is realized by a command from the CPU 102. The impression amount estimation unit 160 estimates the impression amount for the room based on the value indicating the impression amount output by the calculation unit 158. Specifically, the impression amount estimation unit 160 estimates that an impression is good when the value indicating the impression amount is equal to or more than the impression amount threshold value, and makes an impression when the value indicating the impression amount is less than the impression amount threshold value. Is presumed to be bad. The impression amount estimation unit 160 outputs information indicating the estimation result of the impression amount to the output unit 164.
The storage unit 162 is realized by the auxiliary storage device 112. The storage unit 162 stores the estimation formula of the impression amount.
The output unit 164 is realized by the input / output device 108. The output unit 164 outputs the estimation result of the impression amount acquired from the impression amount estimation unit 160. Specifically, the output unit 164 outputs the estimation result of the impression amount to the input / output device 108 such as a display as an evaluation value of openness, an evaluation value of comfort, or an evaluation value of likes and dislikes, or a communication module. It outputs to another device via 110.

(Operation of impression amount estimation device)
FIG. 6 is a flowchart showing an example of the operation of the impression amount estimation device according to the embodiment.
(Step S102) The acquisition unit 152 acquires the input information input when the user operates the input / output device 108. The acquisition unit 152 outputs the acquired input information to the image generation unit 154. As described above, the input information includes the indoor space identification information, the indoor space information, and the date and time information.
(Step S104) When the image generation unit 154 acquires the input information output by the acquisition unit 152, the image generation unit 154 creates a luminance image LI by using the indoor space information and the date and time information included in the acquired input information. In this luminance image LI, an image showing the luminance is shown on the ceiling 1, the left side wall 2, the right side wall 3, the front wall 4, the floor 5, and the window 11 of the room.

(Step S106) The division unit 156 divides the brightness image LI into a ceiling brightness image 1a, a left side wall brightness image 2a, a right side wall brightness image 3a, a front wall brightness image 4a, a floor brightness image 5a, and a window brightness image 11a. ..
(Step S108) The calculation unit 158 determines the number of pixels included in each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a. Calculate. The calculation unit 158 calculates the calculation result of the number of pixels included in each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a. Associate with indoor space identification information.

Further, the calculation unit 158 calculates the brightness for each pixel included in each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a. By calculating the geometric average of the read and read brightness, the ceiling brightness information, the left side wall brightness information, the right side wall brightness information, the front wall brightness information, the floor brightness information, and the window brightness information are obtained.

The calculation unit 158 is based on the calculation result of the number of pixels included in each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a. Calculate the ceiling pixel ratio, left side wall pixel ratio, right side wall pixel ratio, front wall pixel ratio, floor pixel ratio, and window pixel ratio. The calculation unit 158 substitutes each pixel ratio, ceiling brightness information, left side wall brightness information, right side wall brightness information, front wall brightness information, floor brightness information, and window brightness information into the impression amount estimation formula to give an impression. Calculate a value that indicates the quantity.
(Step S110) The impression amount estimation unit 160 estimates the impression amount for the room based on the value indicating the impression amount.

(Example of deriving the estimation formula of impression amount)
An example of deriving the estimation formula of the impression amount will be described.
In order to derive the impression amount estimation formula, windows are arranged in various patterns in the space assuming the LDK, the light environment is simulated, and the impression amount estimation value is calculated. As an example of the estimation formula of the impression amount, the prediction formula obtained from the analysis result of the subject experiment is used.

(Simulation conditions)
FIG. 7 is a diagram showing an outline of the space in which the simulation is performed.
The location of the building is an urban residential area, and it is assumed that the building is a double-decker house that is long from north to south and is surrounded by a two-story neighboring house. The height of the building and the neighboring house was set to X mm. The distance to the neighboring house was set to about Ymm in the east and west, Zmm in the south, and Wmm in the north, assuming a garden to the south of the building and the neighboring house on the north side. For convenience, the plane scale of the building is the same as the plane scale of the simulation space. The simulation space was assumed to be a general LDK space and was set on the first floor of the building, and the scale was J mm in the east-west direction, K mm in the north-south direction, and a ceiling height of L mm. The height of the first floor was M mm from the ground.

(Window pattern)
Windows were arranged in various patterns in the simulation space. The window types were sweep-out windows, high-waist windows (3 types of height), high windows, ground windows (2 types of height), and full-height vertically long windows, and patterns were developed by changing the position and width. The number of patterns is 227 as a total of the east side arrangement and the west side arrangement, and the "impression amount" is calculated for 118 patterns of the east side arrangement.
(Window glass type, window hanging)
The south side sweep-out window is made of transparent glass, and the window hanging is equipped with a lace curtain. For windows other than the south side, the glass type was hazy glass, assuming that the line of sight from the neighboring house would be relaxed, and there was no window hanging except for the bay window. For the sweep-out windows other than the south side, lace curtains were installed in addition to hazy glass.

(Gaze direction, viewpoint)
As shown in FIG. 7, the line-of-sight directions were four directions, north, south, east, and west. The viewpoint position was the center of the plane in the north-south line-of-sight direction, and the position lowered from the center of the plane to the wall behind in the east-west line-of-sight direction. The visual height was uniformly 1500 mm from the floor.
(Times of Day)
The simulation time was set every 30 minutes from 7:00 to 16:00 for the two days of the summer solstice (June 22nd) and the winter solstice (December 22nd).
From the above, the number of simulation calculations performed is 4 directions x 2 days x 19 times = 152 cases for one window arrangement pattern, and the total number of window patterns for the east side arrangement 118 is 17936.

(Creation of 3D model)
The 3D model is mainly focused on reproducing the surface of the simulation space, and the parts that do not affect the light environment are omitted.

(Brightness image analysis)
The data obtained from the calculation results of the ray tracing method was analyzed and converted into data for calculating the estimated value of the impression amount. The data for calculating the estimated value is obtained by dividing the calculation result of the ray tracing method into five constituent surfaces of the ceiling, both side walls, the floor, the front wall, and the window, and then the brightness (logarithmic value) for each pixel. It was assumed that the geometric mean of was calculated. By dividing it into constituent planes, it is possible to develop and examine previous research that the impression changes depending on the brightness of the walls and floor. The constituent planes were divided by separately creating an image in which the portion other than the pixel position corresponding to the constituent plane of each image was masked in black, and multiplying this information when calculating the geometric mean. Further, in the arithmetic mean, when a part of the brightness is conspicuous, the numerical value may be biased and a value different from the actual impression may be evaluated. By using the geometric mean, such a situation can be reduced.

(Creation of impression amount estimation formula)
In parallel with the execution of the window pattern simulation, an estimation formula for the amount of impression was created from the results of the subject experiment. The estimation formula is created by performing multiple regression analysis. When creating the estimation formula, the objective variable is the score of the impression amount of the subject experiment, and the explanatory variable is the geometric mean of the brightness of the five constituent surfaces of the ceiling, both side walls, floor, front wall, and window. A numerical value obtained by multiplying the pixel ratio of the entire image of the surface was used.
From the above, the estimation formula of the impression amount represented by the above-mentioned formula (1) can be obtained.

In the above-described embodiment, the case where the direction of the back side of the paper surface is viewed from the viewpoint 20 on the front side of the paper surface has been described, but the present invention is not limited to this example. For example, it can be applied to the case where the direction on the right side of the paper is viewed from the viewpoint 20 on the front side of the paper, the case where the left side of the paper is viewed, and the like.
Further, in the above-described embodiment, the case where the indoor space includes the ceiling 1, the left side wall 2, the right side wall 3, the front wall 4, the floor 5, the window 11, and the lighting 13 has been described, but the present invention is not limited to this example. .. For example, the interior space may include the ceiling 1, the left side wall 2, the right side wall 3, the front wall 4, the floor 5, and the lighting 13 except for the window 11.
Further, in the above-described embodiment, the image generation unit 154 acquires the indoor space identification information, the indoor space information, and the date and time information from the acquisition unit 152, and uses the acquired indoor space information and the date and time information to obtain the date and time information. A case where a brightness image LI showing an image showing brightness is generated on the ceiling 1, the left side wall 2, the right side wall 3, the front wall 4, the floor 5, and the window 11 of the room at the date and time included in the above has been described. , Not limited to this example. For example, the acquisition unit 152 acquires the captured image of the room input by the user, and outputs the captured image of the acquired room to the image generation unit 154. The image generation unit 154 may generate a luminance image LI from the captured image output by the acquisition unit 152.

Further, in the above-described embodiment, the calculation unit 158 uses the indoor space information and the date and time information to display the brightness on the ceiling 1, the left side wall 2, the right side wall 3, the front wall 4, the floor 5, and the window 11 of the room. Although the case of creating a luminance image showing is described, the present invention is not limited to this example. For example, the calculation unit 158 does not create a brightness image, but each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a. The number of pixels included in may be calculated. Further, for example, the calculation unit 158 may calculate the ceiling brightness information, the side wall brightness information, the front wall brightness information, the floor brightness information, and the window brightness information without creating a brightness image.

Further, in the above-described embodiment, the calculation unit 158 is included in each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a. The case of calculating the geometric average of luminance has been described, but the present invention is not limited to this example. For example, instead of the geometric mean of brightness, a measure of brightness or unpleasant glare may be calculated.
Further, in the above-described embodiment, the case where the estimated value of the impression amount is output from the output unit 164 has been described, but the present invention is not limited to this example. For example, the output unit 164 is configured to acquire predetermined information from either or both of the calculation unit 158 and the impression amount estimation unit 160, and based on the acquired predetermined information, the rendered image, the glare image, and the brightness The image and the brightness image may be displayed.
Further, in the above-described embodiment, when the luminance image is divided into each part of the room and the information for each part of the room entering a specific viewpoint from each part is calculated, as an example, each part of the room has a ceiling. , The case where the constituent surfaces of the room such as the left side wall, the right side wall, the front wall, the floor, and the window are applied has been described, but the present invention is not limited to this example. For example, in the estimated value of the impression amount represented by the formula (1), the portion of the weighting represented by B, C, D, E, F, and G, which has a larger value, may be included. Specifically, when the values of "E", which is the weighting for the front wall brightness information, "F", which is the weighting for the floor brightness information, and "G", which is the weighting for the window brightness information, are large, the room A front wall, a floor, and a window may be applied as each part. When the values of "B", which is the weighting for the ceiling brightness information, "E", which is the weighting for the front wall brightness information, and "G", which is the weighting for the window brightness information, are large, they are used as each part of the room. , Front walls, floors, windows may be applied.

Further, in the above-described embodiment, the case where the shape of the indoor space is a square pillar has been described, but the present invention is not limited to this example. For example, the shape of the indoor space may be an L-shape in which two square pillars are connected.
FIG. 8 is a diagram showing another example of the indoor space. FIG. 8 shows another room including a ceiling 10 (not shown) (not shown), a side wall 6, a side wall 7, a side wall 8, and a floor 9 on the right side wall 3 of the interior space shown in FIG. It is the figure which looked at the interior space which connected the space from the top.
FIG. 9 is a diagram showing another example of the configuration of the interior space of the building. FIG. 9 is a view of the indoor space shown in FIG. 8 as viewed from the viewpoint 20 on the front side of the paper surface toward the back side of the paper surface. According to FIG. 9, when the indoor space shown in FIG. 8 is viewed from the viewpoint 20 on the front side of the paper surface toward the back side of the paper surface, there is an open portion 3b that is not a window on the back side of the right side wall 3. .. It is connected to another indoor space through the open portion 3b. It is assumed that light enters the open portion 3b from lighting (not shown) installed in another indoor space. Further, when there is a window in another indoor space, it is assumed that light enters the open portion 3b from the window. In this case, the open portion 3b is regarded as a side wall or a window, and the above-described calculation is performed. With this configuration, it can be applied not only when the shape of the indoor space is a square pillar, but also when the shape of the indoor space is an L-shape.

(Summary)
According to the impression amount estimation device 100 according to the present embodiment, input information including room lighting information and daylight information is acquired, a brightness image is generated based on the acquired input information, and the generated brightness image is generated. , Divide into information for each part of the room that enters a specific viewpoint from each part of the room. Then, based on the information for each part of the room and the weighting for the information for each part of the room, the value indicating the impression amount is calculated, and the room is based on the value indicating the impression amount obtained by the calculation. Estimate the amount of impression for.

In this way, the brightness image generated based on the input information is divided into information for each part of the room that enters a specific viewpoint from each part of the room. Since the degree of can be easily grasped, it can be applied to space design.
Then, based on the information for each part of the room and the weighting for the information for each part of the room, the value indicating the impression amount is calculated, and the room is based on the value indicating the impression amount obtained by the calculation. The amount of impression on the image can be estimated. That is, the subjective impression amount felt by a person can be estimated from the physical quantity such as the luminance information. Compared to the case where the feeling of brightness of the indoor space is calculated as the average value of the space of interest, it is possible to select the material, color, window, etc. for each constituent surface, so it is possible to design the space. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each constituent surface constituting the indoor space. Since the user can grasp the value indicating the quantified impression amount, the impression amount can be evaluated at a certain level regardless of the experience and sense of the interior advisor.

According to the impression amount estimation device 100 according to the present embodiment, the generated brightness image is obtained from the ceiling information entering a specific viewpoint from the ceiling of the room, the wall information entering the specific viewpoint from the wall of the room, and the floor of the room. It can be divided into floor information that enters a specific viewpoint and window information that enters a specific viewpoint from a room window. Then, a value indicating an impression amount based on the weighting of the ceiling information and the ceiling information, the weighting of the wall information and the wall information, the weighting of the floor information and the floor information, and the weighting of the window information and the window information. Is calculated, and the impression amount for the room can be estimated based on the value indicating the impression amount obtained by the calculation.
In this way, the brightness image generated based on the input information enters a specific viewpoint from the ceiling of the room, wall information entering a specific viewpoint from the wall of the room, and entering a specific viewpoint from the floor of the room. Since it is divided into floor information and window information that enters the specific viewpoint from the window of the room, it is possible to easily grasp the degree of brightness in daily life for each constituent surface such as the ceiling, wall, floor, and window. , Can be applied to space design.
Then, a value indicating an impression amount based on the weighting of the ceiling information and the ceiling information, the weighting of the wall information and the wall information, the weighting of the floor information and the floor information, and the weighting of the window information and the window information. Is calculated, and the impression amount for the room can be estimated based on the value indicating the impression amount obtained by the calculation. That is, the subjective impression amount felt by a person can be estimated from the physical quantity such as the luminance information. Compared to the case where the feeling of brightness of the indoor space is calculated as the average value of the space of interest, it is possible to select the material, color, window, etc. for each constituent surface, so it is possible to design the space. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each constituent surface constituting the indoor space. Since the user can grasp the value indicating the quantified impression amount, the impression amount can be evaluated at a certain level regardless of the experience and sense of the interior advisor.

According to the impression amount estimation device 100 according to the present embodiment, the geometric mean of ceiling information, the geometric mean of wall information, the geometric mean of floor information, and the geometric mean of window information are calculated, and the geometric mean of ceiling information and wall information are calculated. Based on the geometric mean of the floor information, the geometric mean of the floor information, and the geometric mean of the window information, the value indicating the impression amount is calculated, and the impression amount for the room is calculated based on the value indicating the impression amount obtained by the calculation. Can be estimated. That is, the subjective impression amount felt by a person can be estimated from the physical quantity such as the luminance information. Compared to the case where the feeling of brightness of the indoor space is calculated as the average value of the space of interest, it is possible to select the material, color, window, etc. for each constituent surface, so it is possible to design the space. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each constituent surface constituting the indoor space.

(Modification example (1))
When the impression amount estimation device 100 according to the modified example generates the luminance image LI, the brightness image is generated by processing the generated luminance image LI. The impression amount estimation device 100 divides the generated brightness image into constituent surfaces such as a ceiling, a wall, a floor, and a window, and calculates information that enters a specific viewpoint from each constituent surface. As mentioned above, the information that enters a specific viewpoint from the ceiling of the room is called "ceiling information", the information that enters a specific viewpoint from the wall of the room is called "wall information", and the information that enters a specific viewpoint from the floor of the room is called "wall information". Information is called "floor information", and information that enters a specific viewpoint through a window is called "window information". Then, the impression amount estimation device 100 indicates the impression amount of the room based on each of the ceiling information, the wall information, the floor information and the window information, and the weighting for each of the ceiling information, the wall information, the floor information and the window information. Calculate the value. The impression amount estimation device 100 outputs the estimation result of the impression amount for the room based on the value indicating the obtained impression amount by the calculation.

FIG. 2 can be applied to an example of the hardware configuration of the impression amount estimation device 100 according to the modified example.
FIG. 3 can be applied to the functional block diagram of the impression amount estimation device 100 according to the modified example. However, the image generation unit 154 generates a luminance image LI, performs discrete wavelet decomposition on the generated luminance image LI, and corresponds to the roughness of the spatial change for the details calculated at each decomposition level. A brightness image BI is generated by weighting and performing wavelet composition based on the result. The image generation unit 154 outputs the image information of the generated brightness image BI to the division unit 156.

The division unit 156 acquires the image information of the brightness image BI from the image generation unit 154. By performing image processing on the acquired brightness image B1, the dividing portion 156 of the ceiling 1, the left side wall 2, the right side wall 3, the front wall 4, the floor 5, and the window 11. Divide into parts. That is, the division unit 156 acquires the ceiling brightness image 1ab that enters a specific viewpoint from the ceiling of the room by dividing the brightness image BI into the portion of the ceiling 1. Further, the division unit 156 acquires the left side wall brightness image 2ab that enters a specific viewpoint from the left side wall 2 of the room by dividing the brightness image BI into the portion of the left side wall 2. Further, the division unit 156 acquires the right side wall brightness image 3ab that enters a specific viewpoint from the right side wall 3 of the room by dividing the brightness image LI into the right side wall 3. Further, the division unit 156 acquires the front wall brightness image 4ab that enters a specific viewpoint from the front wall 4 of the room by dividing the brightness image LI into the portions of the front wall 4. Further, the division unit 156 acquires the floor brightness image 5ab that enters a specific viewpoint from the floor 5 of the room by dividing the brightness image LI into the floor 5. Further, the division unit 156 acquires the window brightness image 11ab that enters a specific viewpoint from the window 11 of the room by dividing the brightness image LI into the portion of the window 11. As a display example of the brightness image, FIG. 5 can be applied.

The division unit 156 includes image information of the ceiling brightness image 1ab, image information of the left side wall brightness image 2ab, image information of the right side wall brightness image 3ab, image information of the front wall brightness image 4ab, and floor brightness image 5ab. The image information and the window brightness image 11ab are output to the calculation unit 158.
The calculation unit 158 outputs the image information of the ceiling brightness image 1ab, the image information of the left side wall brightness image 2ab, the image information of the right side wall brightness image 3ab, and the image information of the front wall brightness image 4ab output by the division unit 156. And the image information of the floor brightness image 5ab and the window brightness image 11ab are acquired. The calculation unit 158 is a pixel included in each of the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab. Calculate the number. The calculation unit 158 is a pixel included in each of the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab. The calculation result of the number is associated with the indoor space identification information.

Further, the calculation unit 158 refers to each of the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab. The brightness (logarithmic value) of each pixel included in each brightness image is read, and the geometric average of the read brightness is calculated. Here, the geometric mean is obtained by taking the root of the product of the read brightness (the nth root if the number is n). The calculation unit 158 includes a calculation result of the geometric mean of the brightness obtained from the ceiling brightness image 1ab, a calculation result of the geometric mean of the brightness obtained from the left side wall brightness image 2ab, and a right side wall brightness image 3ab. Calculation result of geometric mean of brightness obtained from, calculation result of geometric mean of brightness obtained from front wall brightness image 4ab, calculation of geometric mean of brightness obtained from floor brightness image 5ab The result and the calculation result of the geometric mean of the brightness obtained from the window brightness image 11ab are associated with the indoor space identification information.

Below, the calculation result of the geometric average of the brightness obtained from the ceiling brightness image 1ab is the ceiling brightness information, and the calculation result of the geometric average of the brightness obtained from the left side wall brightness image 2ab is the left side wall brightness information. The calculation result of the geometric average of the brightness obtained from the right side wall brightness image 3ab is the right side wall brightness information, and the calculation result of the geometric average of the brightness obtained from the front wall brightness image 4ab is the front wall brightness information. The calculation result of the geometric average of the brightness obtained from the floor brightness image 5ab is called the floor brightness information, and the calculation result of the geometric average of the brightness obtained from the window brightness image 11ab is called the window brightness information.
The calculation unit 158 is a pixel included in each of the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab. The number of pixels in the entire image is calculated by summing the calculation results of the numbers.

The calculation unit 158 obtains the ceiling pixel ratio by dividing the number of pixels included in the ceiling brightness image 1ab by the number of pixels of the entire image. Further, the calculation unit 158 obtains the left side wall pixel ratio by dividing the number of pixels included in the left side wall brightness image 2ab by the number of pixels of the entire image. Further, the calculation unit 158 obtains the right side wall pixel ratio by dividing the number of pixels included in the right side wall brightness image 3ab by the number of pixels of the entire image. Further, the calculation unit 158 obtains the front wall pixel ratio by dividing the number of pixels included in the front wall brightness image 4ab by the number of pixels of the entire image. Further, the calculation unit 158 obtains the floor pixel ratio by dividing the number of pixels included in the floor brightness image 5ab by the number of pixels of the entire image. Further, the calculation unit 158 obtains the window pixel ratio by dividing the number of pixels included in the window brightness image 11ab by the number of pixels of the entire image.

The calculation unit 158 includes the obtained ceiling pixel ratio, left side wall pixel ratio, right side wall pixel ratio, front wall pixel ratio, floor pixel ratio, and window pixel ratio, and ceiling brightness information, left side wall brightness information, and right side wall brightness. By substituting the ceiling information, the front wall brightness information, the floor brightness information, and the window brightness information into the estimation formula of the impression amount stored in the storage unit 162, the value indicating the impression amount is calculated. Specifically, the estimation formula of the impression amount is expressed by the formula (2). The derivation of the impression amount estimation formula will be described later.

Impression amount estimate = AA + BA (ceiling brightness information x ceiling pixel ratio) + CA (left side wall brightness information x left side wall pixel ratio) + DA (right side wall brightness information x right side wall pixel ratio) + EA (front wall brightness information) × Front wall pixel ratio) + FA (floor brightness information × floor pixel ratio) + GA (window brightness information × window pixel ratio) (2)

In the formula (2), AA, BA, CA, DA, EA, FA, and GA are real numbers and are preset by the administrator of the impression amount estimation device 100. AA is a constant, BA is a weighting for ceiling brightness information, CA is a weighting for left side wall brightness information, DA is a weighting for right side wall brightness information, and EA is a weighting for front wall brightness information. FA is the weighting for the floor brightness information, and GA is the weighting for the window brightness information.
The estimated impressions of AA, BA, CA, DA, EA, FA, and GA are openness, coziness, likes and dislikes, glare, calmness, brightness, cheerfulness, comfort, liveliness, or warmth. It takes a different value depending on whether it is.
The calculation unit 158 outputs a value indicating the impression amount to the impression amount estimation unit 160.

(Operation of impression amount estimation device)
FIG. 6 can be applied to the flowchart showing an example of the operation of the impression amount estimation device according to the modified example. However, in step S104, when the image generation unit 154 acquires the input information output by the acquisition unit 152, the image generation unit 154 creates a luminance image LI using the indoor space information and the date and time information included in the acquired input information. Further, the image generation unit 154 creates a brightness image BI based on the created luminance image LI.
In step S106, the division unit 156 converts the brightness image BI into a ceiling brightness image 1ab, a left side wall brightness image 2ab, a right side wall brightness image 3ab, a front wall brightness image 4ab, a floor brightness image 5ab, and a window. It is divided into brightness images 11ab.
In step S108, the calculation unit 158 includes the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab, respectively. Calculates the number of pixels contained in. The calculation unit 158 is a pixel included in each of the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab. The calculation result of the number is associated with the indoor space identification information.

Further, the calculation unit 158 is included in each of the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab. By reading the brightness for each pixel and calculating the geometric average of the read brightness, ceiling brightness information, left side wall brightness information, right side wall brightness information, front wall brightness information, floor brightness information, And ask for window brightness information.
The calculation unit 158 is a pixel included in each of the ceiling brightness image 1ab, the left side wall brightness image 2ab, the right side wall brightness image 3ab, the front wall brightness image 4ab, the floor brightness image 5ab, and the window brightness image 11ab. From the calculation result of the number, the ceiling pixel ratio, the left side wall pixel ratio, the right side wall pixel ratio, the front wall pixel ratio, the floor pixel ratio, and the window pixel ratio are calculated. The calculation unit 158 substitutes each pixel ratio, ceiling brightness information, side wall brightness information, front wall brightness information, floor brightness information, and window brightness information into the impression amount estimation formula to give an impression. Calculate a value that indicates a quantity.

(Summary)
According to the impression amount estimation device 100 according to the modification, the brightness image generated from the luminance image can be divided into information for each part of the room that enters the specific viewpoint from each part of the room.
In this way, since the brightness image generated from the brightness image is divided into information for each part of the room that enters the specific viewpoint from each part of the room, design is performed for each constituent surface such as each part of the room. be able to.
According to the impression amount estimation device 100 according to the modified example, the brightness image generated from the brightness image is divided into ceiling information that enters a specific viewpoint from the ceiling of the room, wall information that enters a specific viewpoint from the wall of the room, and a room. It can be divided into floor information that enters a specific viewpoint from the floor of the room and window information that enters a specific viewpoint from the window of the room.
In this way, the brightness image generated from the brightness image enters the ceiling information from the ceiling of the room to a specific viewpoint, the wall information from the wall of the room to the specific viewpoint, and the floor from the floor of the room to the specific viewpoint. Since the information is divided into the information and the window information that enters the specific viewpoint from the window of the room, the design can be performed for each constituent surface such as the ceiling, the wall, the floor, and the window.
According to the impression amount estimation device 100 according to the modified example, the geometric mean of ceiling information, the geometric mean of wall information, the geometric mean of floor information, and the geometric mean of window information are calculated, and the geometric mean of ceiling information and the geometric mean of wall information are calculated. Based on the geometric mean, the geometric mean of the floor information, and the geometric mean of the window information, the value indicating the impression amount is calculated, and the impression amount for the room is calculated based on the value indicating the impression amount obtained by the calculation. Can be estimated. That is, the subjective impression amount felt by a person can be estimated from the physical quantity such as the luminance information. Compared to the case where the feeling of brightness of the indoor space is calculated as the average value of the space of interest, it is possible to select the material, color, window, etc. for each constituent surface, so it is possible to design the space. The application is easy, and the impression amount of the indoor space can be easily estimated even when the design is changed for each constituent surface constituting the indoor space.

(Modification example (2))
When the impression amount estimation device 100 according to the modified example generates the luminance image LI, the glare image GI is generated by processing the generated luminance image LI. The impression amount estimation device 100 divides the generated glare image GI into constituent surfaces such as a ceiling, a wall, a floor, and a window, and calculates information that enters a specific viewpoint from each constituent surface. As mentioned above, the information that enters a specific viewpoint from the ceiling of the room is called "ceiling information", the information that enters a specific viewpoint from the wall of the room is called "wall information", and the information that enters a specific viewpoint from the floor of the room is called "wall information". Information is called "floor information", and information that enters a specific viewpoint through a window is called "window information". Then, the impression amount estimation device 100 indicates the impression amount of the room based on each of the ceiling information, the wall information, the floor information and the window information, and the weighting for each of the ceiling information, the wall information, the floor information and the window information. Calculate the value. The impression amount estimation device 100 outputs the estimation result of the impression amount for the room based on the value indicating the obtained impression amount by the calculation.

FIG. 2 can be applied to an example of the hardware configuration of the impression amount estimation device 100 according to the modified example.
FIG. 3 can be applied to the functional block diagram of the impression amount estimation device 100 according to the modified example. However, the image generation unit 154 generates a luminance image LI, and multiplies the image derived by wavelet analysis on the generated luminance image LI by the human perceptual characteristic regarding glare obtained from the experiment. Generates a glare image GI. The image generation unit 154 outputs the image information of the generated glare image GI to the division unit 156.
The division unit 156 acquires the image information of the glare image GI from the image generation unit 154. The divided portion 156 performs image processing on the acquired glare image B1 to perform image processing on the ceiling 1, the left side wall 2, the right side wall 3, the front wall 4, the floor 5, and the window 11. Divide into. That is, the division unit 156 acquires the ceiling glare image 1ac that enters a specific viewpoint from the ceiling of the room by dividing the glare image GI into the portion of the ceiling 1. Further, the division unit 156 acquires the left side wall glare image 2ac that enters a specific viewpoint from the left side wall 2 of the room by dividing the glare image GI into the portion of the left side wall 2. Further, the division unit 156 acquires the right side wall glare image 3ac that enters a specific viewpoint from the right side wall 3 of the room by dividing the glare image GI into the portion of the right side wall 3. Further, the division unit 156 acquires the front wall glare image 4ac entering a specific viewpoint from the front wall 4 of the room by dividing the glare image GI into the portions of the front wall 4. Further, the division unit 156 acquires the floor glare image 5ac entering a specific viewpoint from the floor 5 of the room by dividing the glare image GI into the floor 5. Further, the division unit 156 acquires the window glare image 11ac that enters a specific viewpoint from the window 11 of the room by dividing the glare image GI into the portion of the window 11. FIG. 5 can be applied to the display example of the glare image.

The dividing portion 156 includes image information of the ceiling glare image 1ac, image information of the left side wall glare image 2ac, image information of the right side wall glare image 3ac, image information of the front wall glare image 4ac, image information of the floor glare image 5ac, and window glare. The image 11ac is output to the calculation unit 158.
The calculation unit 158 outputs the image information of the ceiling glare image 1ac, the image information of the left side wall glare image 2ac, the image information of the right side wall glare image 3ac, the image information of the front wall glare image 4ac, and the floor glare image output by the division unit 156. The image information of 5ac and the window glare image 11ac are acquired. The calculation unit 158 calculates the number of pixels included in each of the ceiling glare image 1ac, the left side wall glare image 2ac, the right side wall glare image 3ac, the front wall glare image 4ac, the floor glare image 5ac, and the window glare image 11ac. The calculation unit 158 calculates the number of pixels included in each of the ceiling glare image 1ac, the left side wall glare image 2ac, the right side wall glare image 3ac, the front wall glare image 4ac, the floor glare image 5ac, and the window glare image 11ac. Associate with indoor space identification information.

Further, the calculation unit 158 is included in each glare image for each of the ceiling glare image 1ac, the left side wall glare image 2ac, the right side wall glare image 3ac, the front wall glare image 4ac, the floor glare image 5ac, and the window glare image 11ac. Calculate the maximum glare value. For example, the calculation unit 158 evaluates the maximum value of glare caused by daylight by using Glare Index (GI), Bright Day light Glare Index (BGI), CIE Glare Index (CGI), Predicted Glare Sensation Vote (PG), etc. Calculate using. Further, the calculation unit 158 may calculate a value calculated from an evaluation method such as GI, BGI, CGI, PGSV, etc. by using a value converted into a Unified Glare Rating (UGR). The calculation unit 158 includes the maximum value of glare obtained from the ceiling glare image 1ac, the maximum value of glare obtained from the left side wall glare image 2ac, the maximum value of glare obtained from the right side wall glare image 3ac, and the front surface. The maximum value of glare obtained from the wall glare image 4ac, the maximum value of glare obtained from the floor glare image 5ac, and the maximum value of glare obtained from the window glare image 11ac are associated with the indoor space identification information.
Below, the maximum value of glare obtained from the ceiling glare image 1ac is the ceiling glare information, the maximum value of the glare obtained from the left side wall glare image 2ac is the left side wall glare information, and the maximum value of the glare obtained from the right side wall glare image 3ac. The value is obtained from the right side wall glare information, the maximum value of glare obtained from the front wall glare image 4ac is obtained from the front wall glare information, the maximum value of glare obtained from the floor glare image 5ac is obtained from the floor glare information, and the window glare image 11ac. The maximum value of glare is called window glare information.

The calculation unit 158 substitutes the ceiling glare information, the left side wall glare information, the right side wall glare information, the front wall glare information, the floor glare information, and the window glare information into the impression amount estimation formula stored in the storage unit 162. By doing so, a value indicating the amount of impression is calculated. Specifically, the estimation formula of the impression amount is expressed by the formula (3). The derivation of the impression amount estimation formula will be described later.

Estimated value of impression amount = AC + BC (ceiling glare information) + CC (left side wall glare information) + DC (right side wall glare information) + EC (front wall glare information) + FC (floor glare information) + GC (window glare information) (3)

In the formula (3), AC, BC, CC, DC, EC, FC, and GC are real numbers and are preset by the administrator of the impression amount estimation device 100. AC is a constant, BC is a weighting for ceiling glare information, CC is a weighting for left side wall glare information, DC is a weighting for right side wall glare information, EC is a weighting for front wall glare information, FC Is the weighting for the floor glare information, and GC is the weighting for the window glare information.
The estimated impressions of AC, BC, CC, DC, EC, FC, and GC are openness, coziness, likes and dislikes, glare, calmness, brightness, cheerfulness, comfort, liveliness, or warmth. It takes a different value depending on whether it is.
The calculation unit 158 outputs a value indicating the impression amount to the impression amount estimation unit 160.

(Operation of impression amount estimation device)
FIG. 6 can be applied to the flowchart showing an example of the operation of the impression amount estimation device according to the modified example. However, in step S104, when the image generation unit 154 acquires the input information output by the acquisition unit 152, the image generation unit 154 creates a luminance image LI using the indoor space information and the date and time information included in the acquired input information. Further, the image generation unit 154 creates a glare image GI based on the created luminance image LI.
In step S106, the division unit 156 divides the glare image GI into a ceiling glare image 1ac, a left side wall glare image 2ac, a right side wall glare image 3ac, a front wall glare image 4ac, a floor glare image 5ac, and a window glare image 11ac. ..
In step S108, the calculation unit 158 calculates the maximum values of the ceiling glare image 1ac, the left side wall glare image 2ac, the right side wall glare image 3ac, the front wall glare image 4ac, the floor glare image 5ac, and the window glare image 11ac. .. The calculation unit 158 identifies the maximum values included in each of the ceiling glare image 1ac, the left side wall glare image 2ac, the right side wall glare image 3ac, the front wall glare image 4ac, the floor glare image 5ac, and the window glare image 11ac. Associate with information.

Further, the calculation unit 158 includes the maximum value of glare included in each of the ceiling glare image 1ac, the left side wall glare image 2ac, the right side wall glare image 3ac, the front wall glare image 4ac, the floor glare image 5ac, and the window glare image 11ac. The calculation unit 158 that obtains reading, ceiling glare information, left side wall glare information, right side wall glare information, front wall glare information, floor glare information, and window glare information is used to obtain ceiling glare image 1ac, left side wall glare image 2ac, and right side wall glare. The maximum value included in each of the image 3ac, the front wall glare image 4ac, the floor glare image 5ac, and the window glare image 11ac is calculated. The calculation unit 158 calculates a value indicating the impression amount by substituting the ceiling glare information, the side wall glare information, the front wall glare information, the floor glare information, and the window glare information into the impression amount estimation formula.
In the above-described modification, the calculation unit 158 has the maximum value of glare obtained from the ceiling glare image 1ac, the maximum value of glare obtained from the left side wall glare image 2ac, and the glare obtained from the right side wall glare image 3ac. The maximum value of the glare, the maximum value of the glare obtained from the front wall glare image 4ac, the maximum value of the glare obtained from the floor glare image 5ac, and the maximum value of the glare obtained from the window glare image 11ac. The case of associating with the spatial identification information has been described, but the present invention is not limited to this example. For example, instead of using the maximum value of glare, the threshold value (evaluation point) of glare in question may be associated with the indoor space identification information. Here, when the value proposed by the evaluation method used is used, the threshold value may be a value "22" that begins to feel unpleasant in the value converted into UGR, for example. When other evaluation methods are used, the value at which each person begins to feel uncomfortable may be set as the threshold value.

(Summary)
According to the impression amount estimation device 100 according to the modification, the glare image generated from the luminance image can be divided into information for each part of the room that enters the specific viewpoint from each part of the room.
In this way, the glare image generated from the luminance image is divided into information for each part of the room that enters the specific viewpoint from each part of the room, so design is performed for each constituent surface such as each part of the room. Can be done.
According to the impression amount estimation device 100 according to the modified example, the glare image generated from the brightness image is divided into ceiling information that enters a specific viewpoint from the ceiling of the room, wall information that enters a specific viewpoint from the wall of the room, and room. It can be divided into floor information that enters a specific viewpoint from the floor and window information that enters a specific viewpoint from the window of the room.
In this way, the glare image generated from the brightness image enters the specific viewpoint from the ceiling of the room, the wall information that enters the specific viewpoint from the wall of the room, and the floor information that enters the specific viewpoint from the floor of the room. And the window information that enters the specific viewpoint from the window of the room, so that the design can be performed for each constituent surface such as the ceiling, the wall, the floor, and the window.

According to the impression amount estimation device 100 according to the modified example, the maximum value of the ceiling information, the maximum value of the wall information, the maximum value of the floor information, and the maximum value of the window information are calculated, and the maximum value of the ceiling information and the maximum value of the wall information are calculated. Based on the maximum value, the maximum value of the floor information, and the maximum value of the window information, the value indicating the impression amount is calculated, and the impression amount for the room is calculated based on the value indicating the impression amount obtained by the calculation. Can be estimated. That is, the subjective impression amount felt by a person can be estimated from the physical quantity such as the luminance information. Since the discomfort caused by the glare of the indoor space can be evaluated for each constituent surface, it is possible to easily determine whether glare is a problem in terms of the line of sight, which makes it easy to apply to space design and indoors. Even when the design is changed for each constituent surface that constitutes the space, the impression amount of the indoor space can be easily estimated.

(Modification example (3))
In the above-described embodiment, the impression amount estimation device 200 according to the modified example stores the above-mentioned luminance image LI in association with the indoor space identification information. For example, the luminance image LI is generated by using the radiosity method, the ray tracing method, or the like, and is stored in the impression amount estimation device 200 by the administrator.
When the impression amount estimation device 200 according to the modification acquires the indoor space identification information input by the user of the impression amount estimation device 200, the luminance image LI stored in association with the acquired indoor space identification information is acquired. The impression amount estimation device 200 divides the acquired luminance image LI into a ceiling 1, a left side wall 2, a right side wall 3, a front wall 4, a floor 5, and a window 11. As a result, the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a are acquired.

The impression amount estimation device 200 calculates the number of pixels included in each of the acquired luminance images. Further, the impression amount estimation device 200 calculates ceiling brightness information, left side wall brightness information, right side wall brightness information, front wall brightness information, floor brightness information, and window brightness information from each of the acquired brightness images. The impression amount estimation device 200 according to the modified example is based on the calculation result of the number of pixels and the ceiling brightness information, the left side wall brightness information, the right side wall brightness information, the front wall brightness information, the floor brightness information, and the window brightness information. The value indicating the amount of impression is calculated, and the amount of impression is estimated based on the value indicating the amount of impression obtained by the calculation.

FIG. 2 can be applied to the hardware configuration of the impression amount estimation device 200 according to the modified example.
(Functional configuration of impression amount estimation device)
FIG. 10 is a functional block diagram of the impression amount estimation device according to the modified example.
The impression amount estimation device 200 outputs the acquisition unit 252, the division unit 256, the calculation unit 258, the impression amount estimation unit 260, the storage unit 262, and the output by executing the program developed on the RAM 106 from the auxiliary storage device 112 by the CPU 102. It functions as a unit 264.

(Each functional configuration of the impression amount estimation device)
Each functional configuration of the impression amount estimation device 200 will be described in detail with reference to FIGS. 2 and 10. In the following description of each function of the impression amount estimation device 200, the relationship with the main hardware for realizing each functional block of the impression amount estimation device 200 shown in FIG. 10 will also be described.

The acquisition unit 152 described above can be applied to the acquisition unit 252. However, the acquisition unit 252 acquires the input information input by the user from the input / output device 108. The input information includes indoor space identification information. When the impression amount estimation device 100 is activated, a screen for inputting indoor space identification information to the input / output device 108 is displayed. On the screen where the user inputs the indoor space identification information, the indoor space identification information of the indoor space for which the impression amount is to be estimated is input. The acquisition unit 252 outputs the indoor space identification information input by the user operating the input / output device 108 to the impression amount estimation unit 260.

As the division unit 256, the division unit 156 described above can be applied. However, when the division unit 256 acquires the indoor space identification information output by the acquisition unit 252, the division unit 256 acquires the luminance image LI associated with the acquired indoor space identification information from the storage unit 262.
By performing image processing on the acquired luminance image LI, the division portion 256 performs an image processing on the ceiling 1, the left side wall 2, the right side wall 3, the front wall 4, the floor 5, and the window 11. By dividing into the above, the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a are acquired.
The calculation unit 258 can apply the above-mentioned calculation unit 158. However, the calculation unit 258 calculates the number of pixels included in each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a. .. Further, the calculation unit 258 obtains the number of pixels of the entire image by summing the calculation results of the number of pixels included in each of the luminance images.

The calculation unit 258 obtains the ceiling pixel ratio by dividing the number of pixels included in the ceiling brightness image 1a by the number of pixels of the entire image. Further, the calculation unit 258 obtains the left side wall pixel ratio by dividing the number of pixels included in the left side wall brightness image 2a by the number of pixels of the entire image. Further, the calculation unit 258 obtains the right side wall pixel ratio by dividing the number of pixels included in the right side wall brightness image 3a by the number of pixels of the entire image. Further, the calculation unit 258 obtains the front wall pixel ratio by dividing the number of pixels included in the front wall brightness image 4a by the number of pixels of the entire image. Further, the calculation unit 258 obtains the floor pixel ratio by dividing the number of pixels included in the floor brightness image 5a by the number of pixels of the entire image. Further, the calculation unit 258 obtains the window pixel ratio by dividing the number of pixels included in the window brightness image 11a by the number of pixels of the entire image.

Further, the calculation unit 258 is included in each brightness image for each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a. By reading the brightness of each pixel and calculating the geometric average of the read brightness, the ceiling brightness information, the left side wall brightness information, the right side wall brightness information, the front wall brightness information, the floor brightness information, and the window brightness information are obtained.
The calculation unit 258 includes a ceiling pixel ratio, a left side wall pixel ratio, a right side wall pixel ratio, a front wall pixel ratio, a floor pixel ratio, and a window pixel ratio, and ceiling brightness information, left side wall brightness information, right side wall brightness information, and front wall. By substituting the brightness information, the floor brightness information, and the window brightness information into the equation (1) which is the estimation formula of the impression amount stored in the storage unit 262, the value indicating the impression amount is calculated.

The impression amount estimation unit 260 can apply the impression amount estimation unit 160 described above. However, the impression amount estimation unit 260 estimates the impression amount based on the value indicating the impression amount output by the calculation unit 158. The impression amount estimation unit 260 outputs the impression amount estimation result to the output unit 264.
As the storage unit 262, the storage unit 162 described above can be applied. The storage unit 262 stores the estimation formula of the impression amount. Further, the storage unit 262 stores the luminance image LI in association with the indoor space identification information.
The output unit 164 described above can be applied to the output unit 264. The output unit 264 outputs the estimation result of the impression amount acquired from the impression amount estimation unit 260. Specifically, the output unit 264 outputs an impression amount estimation result, an evaluation value of openness, an evaluation value of comfort, or an evaluation value of likes and dislikes to an input / output device 108 such as a display, or a communication module 110. Output to other devices via.

(Operation of impression amount estimation device)
FIG. 11 is a flowchart showing an example of the operation of the impression amount estimation device according to the modified example.
(Step S202) The acquisition unit 252 acquires the input information input by the user operating the input / output device 108. The acquisition unit 252 outputs the acquired input information to the division unit 256. As described above, the input information includes the indoor space identification information.
(Step S204) When the dividing unit 256 acquires the input information output by the acquisition unit 252, the division unit 256 uses the indoor space information included in the acquired input information to obtain the brightness associated with the indoor space information from the storage unit 262. Acquire the image LI.

(Step S206) The division unit 256 divides the brightness image LI into a ceiling brightness image 1a, a left side wall brightness image 2a, a right side wall brightness image 3a, a front wall brightness image 4a, a floor brightness image 5a, and a window brightness image 11a. ..
(Step S208) The calculation unit 258 determines the number of pixels included in each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a. Calculate.
Further, the calculation unit 258 calculates the brightness for each pixel included in each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a. By calculating the geometric average of the read and read brightness, the ceiling brightness information, the left side wall brightness information, the right side wall brightness information, the front wall brightness information, the floor brightness information, and the window brightness information are obtained.
The calculation unit 258 is based on the calculation result of the number of pixels included in each of the ceiling brightness image 1a, the left side wall brightness image 2a, the right side wall brightness image 3a, the front wall brightness image 4a, the floor brightness image 5a, and the window brightness image 11a. Calculate the ceiling pixel ratio, left side wall pixel ratio, right side wall pixel ratio, front wall pixel ratio, floor pixel ratio, and window pixel ratio. The calculation unit 258 uses the ceiling brightness information, the left side wall brightness information, the left side wall brightness information, the front wall brightness information, the floor brightness information, and the window brightness information as an expression for estimating the impression amount (1). ) Is used to calculate the value indicating the impression amount. The calculation unit 258 outputs a value indicating the impression amount to the impression amount estimation unit 260.
(Step S210) The impression amount estimation unit 160 estimates the impression amount based on the value indicating the impression amount output by the calculation unit 158.

In this modification, the case where the impression amount estimation device 200 stores the luminance image LI in association with the indoor space identification information has been described, but the present invention is not limited to this example. For example, the brightness image BI may be stored or the glare image GI may be stored in association with the indoor space identification information.
According to the impression amount estimation device 200 according to the modified example, the luminance image LI is stored in association with the indoor space identification information. As a result, when the impression amount estimation device 200 according to the modified example acquires the indoor space identification information input by the user of the impression amount estimation device 200, it is based on the luminance image LI stored in association with the acquired indoor space identification information. The amount of impression can be estimated. That is, according to the impression amount estimation device 200 according to the modified example, by storing the luminance image LI in association with the indoor space identification information, the impression amount estimation result can be referred to when it is desired to be referred to. ..

Although the embodiments and modifications thereof have been described above, these embodiments and modifications thereof are presented as examples and are not intended to limit the scope of the invention. These embodiments and variations thereof can be implemented in various other embodiments, and various omissions, replacements, changes, and combinations can be made without departing from the gist of the invention. These embodiments and variations thereof are included in the scope and gist of the invention, and at the same time, are included in the scope of the invention described in the claims and the equivalent scope thereof. For example, the impression amount estimation device or the impression amount estimation method executed by the computer device can be realized as a building design method executed by the computer device.
For example, in the embodiment and its modified example, the case where the front wall can be seen when the interior space of the building is viewed from the viewpoint 20 has been described, but the present invention is not limited to this example. For example, it can be applied even when the front wall cannot be seen when looking at the interior space of the building.
FIG. 12 is a diagram showing an example of the configuration of the interior space of the building. In the example shown in FIG. 12, when the interior space of the building is viewed from the viewpoint 20, the front wall cannot be seen. Even in such a case, the impression amount can be estimated by setting the constituent surfaces such as the ceiling, the floor, the side walls, and the windows, as in the above-described embodiment and its modification.

The impression amount estimation device 100 and the impression amount estimation device 200 described above are realized by a computer as described above. In this case, a program for realizing the function of each functional block is recorded on a computer-readable recording medium. The program recorded on the recording medium may be read by the computer system and executed by the CPU. The term "computer system" as used herein includes hardware such as an OS (Operating System) and peripheral devices.
Further, the "computer-readable recording medium" refers to a portable medium such as a flexible disk, a magneto-optical disk, a ROM, or a CD-ROM. Further, the "computer-readable recording medium" includes a storage device such as a hard disk built in a computer system.

Further, the "computer-readable recording medium" may include a medium that dynamically holds the program for a short period of time. What dynamically holds the program for a short period of time is, for example, a communication line when the program is transmitted via a network such as the Internet or a communication line such as a telephone line.
Further, the "computer-readable recording medium" may include a medium that holds a program for a certain period of time, such as a volatile memory inside a computer system serving as a server or a client.
Further, the above program may be for realizing a part of the above-mentioned functions. Further, the above-mentioned program may be realized by combining the above-mentioned functions with a program already recorded in the computer system.
Further, the above program may be realized by using a programmable logic device. The programmable logic device is, for example, an FPGA (Field Programmable Gate Array).

The impression amount estimation device 100 and the impression amount estimation device 200 described above have a computer inside. The process of each process of the impression amount estimation device 100 described above is stored in a computer-readable recording medium in the form of a program, and the process is performed by the computer reading and executing this program. Here, the computer-readable recording medium refers to a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, a semiconductor memory, or the like. Further, this computer program may be distributed to a computer via a communication line, and the computer receiving the distribution may execute the program.
Further, the above program may be for realizing a part of the above-mentioned functions.
Further, it may be a so-called difference file (difference program) that can realize the above-mentioned function in combination with a program already recorded in the computer system.

1, 10 ... Ceiling, 1a ... Ceiling brightness image, 2 ... Left side wall, 2a ... Left side wall brightness image, 2ab ... Left side wall brightness image, 2ac ... Left side wall glare image, 3 ... Right side wall, 3a ... Right side wall brightness image 3, 3ab ... Right side wall brightness image, 3ac ... Right side wall glare image, 3b ... Open area, 4 ... Front wall, 4a ... Front wall brightness image, 4ab ... Front wall brightness image, 4ac ... Front wall glare image, 5, 9 ... Floor, 5a ... Floor brightness image, 5ab ... Floor brightness image, 5ac ... Floor glare image, 6, 7, 8 ... Side wall, 11 ... Window, 11a ... Window brightness image, 11ab ... Window brightness image, 11ac ... Window glare image, 13 ... Lighting, 20 ... Viewpoint, 100, 200 ... Impression amount estimation device, 102 ... CPU, 104 ... ROM, 106 ... RAM, 108 ... Input / output device, 110 ... Communication module, 112 ... Auxiliary storage device , 120 ... Bus, 152, 252 ... Acquisition unit, 154 ... Image generation unit, 156, 256 ... Division unit, 158, 258 ... Calculation unit, 160, 260 ... Impression amount estimation unit, 162, 262 ... Storage unit, 164, 264 ... Output unit, 170 ... Input screen

Claims (10)

A computer device is an impression amount estimation method that estimates an impression amount for a room recognized from a specific viewpoint.
A step in which the computer device acquires input information including room lighting information and daylight information.
A step in which the computer device generates a luminance image based on the input information.
A step in which the computer device divides the luminance image into information for each part of the room that enters a specific viewpoint from each part of the room.
An impression amount estimation method, wherein the computer device includes a step of calculating a value indicating an impression amount based on a weighting of information for each part of the room and information for each part of the room. In the dividing step, the computer device obtains the brightness image from the ceiling of the room into the specific viewpoint, the wall information from the wall of the room into the specific viewpoint, and the floor of the room. It is divided into the floor information that enters the specific viewpoint from the above and the window information that enters the specific viewpoint from the window of the room.
In the calculation step, the computer device performs weighting on the ceiling information and the ceiling information, weighting on the wall information and the wall information, weighting on the floor information and the floor information, and the window information and the window. The impression amount estimation method according to claim 1, wherein a value indicating an impression amount is calculated based on weighting of information. The computer device has a step of generating a brightness image from the brightness image generated in the step of generating the brightness image.
The impression amount estimation method according to claim 1, wherein in the dividing step, the computer device divides the brightness image into information for each part of the room that enters a specific viewpoint from each part of the room. In the dividing step, the computer device obtains the brightness image from the ceiling of the room into the specific viewpoint, ceiling information from the wall of the room into the specific viewpoint, and the wall information of the room. It is divided into floor information that enters the specific viewpoint from the floor and window information that enters the specific viewpoint from the window of the room.
In the calculation step, the computer device performs weighting on the ceiling information and the ceiling information, weighting on the wall information and the wall information, weighting on the floor information and the floor information, and the window information and the window. The impression amount estimation method according to claim 3, wherein a value indicating the impression amount is calculated based on the weighting of the information. In the calculation step, the computer device calculates the geometric mean of the ceiling information, the geometric mean of the wall information, the geometric mean of the floor information, and the geometric mean of the window information, and the geometric mean of the ceiling information, The impression amount estimation method according to claim 2 or 4, further calculated based on the geometric mean of the wall information, the geometric mean of the floor information, and the geometric mean of the window information. The computer device has a step of generating a glare image from the luminance image generated in the step of generating the luminance image.
The impression amount estimation method according to claim 1, wherein in the dividing step, the glare image is divided into information for each part of the room that enters a specific viewpoint from each part of the room. In the dividing step, the computer device obtains the glare image into the ceiling information entering the specific viewpoint from the ceiling of the room, the wall information entering the specific viewpoint from the wall of the room, and the floor of the room. The impression amount estimation method according to claim 6, wherein the floor information entering the specific viewpoint and the window information entering the specific viewpoint from the window of the room are divided. In the calculation step, the computer device calculates the maximum value of the ceiling information, the maximum value of the wall information, the maximum value of the floor information, and the maximum value of the window information, and the maximum value of the ceiling information, The impression amount estimation method according to claim 7, further calculating based on the maximum value of the wall information, the maximum value of the floor information, and the maximum value of the window information. It is an impression amount estimation device that estimates the impression amount for a room recognized from a specific viewpoint.
An acquisition unit that acquires input information including room lighting information and daylight information,
A generator that generates a luminance image based on the input information,
A partition portion that divides the luminance image into information for each part of the room that enters the specific viewpoint from each part of the room, and
An impression amount estimation device including a calculation unit that calculates a value indicating an impression amount based on the information for each part of the room and the information for each part of the room. A building design method executed by a computer device, which has the impression amount estimation method according to any one of claims 1 to 8.

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