WO2022009512A1 - Brightness feeling prediction device and brightness feeling prediction program - Google Patents

Brightness feeling prediction device and brightness feeling prediction program Download PDF

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Publication number
WO2022009512A1
WO2022009512A1 PCT/JP2021/017650 JP2021017650W WO2022009512A1 WO 2022009512 A1 WO2022009512 A1 WO 2022009512A1 JP 2021017650 W JP2021017650 W JP 2021017650W WO 2022009512 A1 WO2022009512 A1 WO 2022009512A1
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brightness
image
feeling
target space
surface type
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PCT/JP2021/017650
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French (fr)
Japanese (ja)
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英司 山本
誠司 奥村
智祐 成井
利宏 妻鹿
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三菱電機株式会社
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J1/00—Photometry, e.g. photographic exposure meter
    • G01J1/42—Photometry, e.g. photographic exposure meter using electric radiation detectors
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • H—ELECTRICITY
    • H05—ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR
    • H05B—ELECTRIC HEATING; ELECTRIC LIGHT SOURCES NOT OTHERWISE PROVIDED FOR; CIRCUIT ARRANGEMENTS FOR ELECTRIC LIGHT SOURCES, IN GENERAL
    • H05B47/00—Circuit arrangements for operating light sources in general, i.e. where the type of light source is not relevant
    • H05B47/10—Controlling the light source
    • H05B47/105—Controlling the light source in response to determined parameters
    • H05B47/11—Controlling the light source in response to determined parameters by determining the brightness or colour temperature of ambient light
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B20/00—Energy efficient lighting technologies, e.g. halogen lamps or gas discharge lamps
    • Y02B20/40—Control techniques providing energy savings, e.g. smart controller or presence detection

Definitions

  • the present invention relates to a brightness feeling prediction device and a brightness feeling prediction program.
  • the sense of brightness is the amount of brightness that humans perceive, and is an index different from the illuminance, which is a physical quantity that represents the brightness of light that illuminates the surface of an object. Therefore, for example, even if the illuminance of the lighting installed in the space is large, the feeling of brightness for the space is not always large.
  • Patent Document 1 discloses a brightness feeling predicting device that predicts the brightness feeling of the space based on the brightness of each pixel included in the image of the target space that is the object for predicting the brightness feeling. Has been done.
  • Patent Document 2 discloses a brightness feeling predicting device that predicts the brightness feeling of the space based on the illuminance at a point on a vertical surface in the target space.
  • An object of the present invention is to predict the brightness of the target space with high accuracy.
  • the surface type setting unit that sets the surface type of each image area corresponding to each surface included in the luminance image representing the target space, and the weight indicating the degree of contribution to the feeling of brightness for each surface type are used.
  • the brightness feeling of the target space is based on the luminance values of the plurality of pixels included in the image region and the weights of the surface types of the image region for each of the plurality of image regions. It is a brightness feeling prediction device characterized by including a brightness feeling prediction unit for predicting.
  • the brightness prediction unit is located in the vicinity of the representative value of the luminance values of the plurality of pixels included in the first image region and the vicinity of the first image region in the luminance image among the plurality of image regions. It is characterized in that the feeling of brightness of the target space is predicted based on the ratio of the luminance values of the plurality of pixels included in the second image region to the representative values.
  • the brightness prediction unit includes a representative value of the luminance values of a plurality of pixels included in the image region whose surface type is the floor surface among the plurality of image regions, and a plurality of brightness values included in the other image regions. It is characterized in that the feeling of brightness of the target space is predicted without considering the ratio of the brightness value of the pixel to the representative value.
  • the brightness feeling predicting unit intermittently predicts the brightness feeling of the target space, and the brightness feeling of the target space predicted immediately before and the brightness feeling of the target space predicted this time. It is characterized in that the brightness feeling of the target space predicted this time is corrected based on the difference between the above.
  • the present invention comprises a surface type setting unit for setting a surface type of each image area corresponding to each surface included in a luminance image representing a target space, and a contribution to a sense of brightness for each surface type.
  • the target is based on the brightness values of the plurality of pixels included in the image region and the weight of the surface type of the image region for each of the plurality of image regions. It is a brightness prediction program characterized by functioning as a brightness prediction unit that predicts the brightness of a space.
  • the feeling of brightness of the target space can be predicted with high accuracy.
  • FIG. 1 is a schematic configuration diagram of the brightness feeling prediction device 10 according to the present embodiment.
  • the brightness feeling prediction device 10 is, for example, a server computer, a personal computer, a tablet terminal, or the like, but may be any device as long as the functions described below can be exhibited. Further, although the brightness feeling prediction device 10 according to the present embodiment exerts each function described below in one device, each function of the brightness feeling prediction device 10 may be exerted by a plurality of devices.
  • the communication unit 12 is configured to include, for example, a network adapter.
  • the communication unit 12 exhibits a function of communicating with another device (for example, a camera or an image processing device that processes an image captured by the camera) via a communication line such as a LAN or the Internet.
  • another device for example, a camera or an image processing device that processes an image captured by the camera
  • the communication unit 12 receives the luminance image 20 described later from another device.
  • the communication unit 12 may transmit the prediction result by the brightness feeling prediction unit 28, which will be described later, to another device.
  • the display unit 14 includes, for example, a liquid crystal display, an organic EL display, and the like.
  • the display unit 14 displays various screens.
  • the display unit 14 can display the luminance image 20 and the prediction result by the brightness feeling prediction unit 28.
  • the input unit 16 includes, for example, a mouse, a keyboard, a touch panel, a microphone, and the like.
  • the input unit 16 is used to input an instruction from the user to the brightness feeling prediction device 10.
  • the storage unit 18 includes, for example, a hard disk, SSD, ROM, RAM, or the like.
  • the storage unit 18 stores a brightness prediction program for operating each unit of the brightness prediction device 10. Further, as shown in FIG. 1, the luminance image 20 and the weight information 22 are stored in the storage unit 18.
  • the brightness image 20 is an image representing a target space, which is a space for which a brightness feeling is predicted by the brightness feeling prediction device 10.
  • the target space in the present specification is a space including a plurality of types of surfaces (for example, a wall surface, a ceiling surface, a floor surface, etc.).
  • the target space is an indoor space.
  • FIG. 2 shows an example of the luminance image 20.
  • the luminance image 20 is a two-dimensional array of a plurality of pixels. Each pixel included in the luminance image 20 may have at least a luminance value as a pixel value.
  • the luminance image 20 may be a camera image obtained by photographing the target space with a camera. Further, in the camera image, the range (range) of the brightness value of each pixel is relatively narrow (for example, 0 to 255), whereas in the brightness image 20, the luminance is processed to expand the luminance range of each pixel of the camera image. It is preferable that it is an extended image.
  • the luminance image 20 may be an image formed by a computer program, for example, a CG image, instead of an image based on a camera image.
  • the brightness feeling prediction device 10 receives the luminance image 20 from another device by the communication unit 12 described above and stores it in the storage unit 18. Alternatively, the brightness feeling prediction device 10 may form the luminance image 20.
  • the weight information 22 is information in which a weight indicating the degree of contribution to the feeling of brightness is associated with each surface type that can be defined in the luminance image 20.
  • the target space includes a plurality of types of surfaces, but the inventor of the present invention has a surface according to the surface type included in the target space based on the results of a survey such as a questionnaire. It was found that the influence of the brightness value of each pixel included in the above on the feeling of brightness of the target space, that is, the degree of contribution to the feeling of brightness is different. Therefore, the weight indicating the degree of contribution to the feeling of brightness for each surface type based on the survey result is stored in the storage unit 18 in advance as the weight information 22.
  • FIG. 3 shows an example of the weight information 22.
  • FIG. 3 shows a ceiling surface, a front wall surface, a side wall surface, and a floor surface as surface types.
  • the ceiling surface is a surface corresponding to the ceiling of the target space
  • the front wall surface is a surface corresponding to the wall extending in the left-right direction of the brightness image 20 in the field of view of the brightness image 20
  • the side wall surface is the surface corresponding to the brightness.
  • the floor surface is the surface corresponding to the floor of the target space.
  • the surface type is not limited to these, and other types of surfaces (for example, window surfaces) may be included.
  • the invention of the present invention states that the degree of contribution to the sense of brightness of the target space is in the order of front wall surface, ceiling surface, side wall surface, and floor surface from the largest. Found. Therefore, among the four surface types, the weight of the front wall surface is the largest, the weight of the ceiling surface is the next largest, the weight of the side wall surface is the next largest, and the weight of the floor surface is the smallest.
  • the actual value of the weight is an example, and may be appropriately changed according to an equation for calculating the feeling of brightness.
  • control unit 24 includes, for example, various control devices such as a CPU, GPU, ASIC, and FPGA.
  • the control unit 24 controls each unit of the brightness sensation prediction device 10 based on the brightness sensation prediction program stored in the storage unit 18.
  • the control unit 24 functions as a surface type setting unit 26 and a brightness feeling prediction unit 28.
  • the surface type setting unit 26 first defines each image area corresponding to each surface included in the luminance image 20.
  • the surface type setting unit 26 defines a plurality of image regions by performing image analysis on the luminance image 20. Specifically, the surface type setting unit 26 performs edge detection processing on the luminance image 20, and sets the region surrounded by the detected edge or the region surrounded by the detected edge and the side of the luminance image 20 as 1. Defined as one image area. At this time, the area below the predetermined area (number of pixels) may be ignored without being defined as an image area. As a result, objects other than the surface included in the luminance image 20 (for example, furniture, pillars, etc.) can be excluded. Further, the surface type setting unit 26 may define a plurality of image areas in the luminance image 20 according to an instruction from the user without performing image processing on the luminance image 20.
  • the surface type setting unit 26 sets the surface types of a plurality of defined image areas.
  • the surface type setting unit 26 sets the surface type based on the shape of the defined image area and the position in the luminance image 20.
  • the surface type setting unit 26 is a trapezoidal image region in which the upper base and the lower base are parallel to each other, the upper base is longer than the lower base, and the image region is located on the upper side in the luminance image 20.
  • the surface type setting unit 26 is a quadrangular image region, and the surface type of the image region in which at least one side on the left and right sides is vertical (extended in the vertical direction in the luminance image 20) is referred to as a side wall surface.
  • the surface type setting unit 26 may specify the surface type of each image area according to an instruction from the user, regardless of the shape of the defined image area or the position in the luminance image 20.
  • FIG. 4 shows a plurality of image regions 40 defined in the luminance image 20 shown in FIG. 2 and surface types of each image region 40.
  • the ceiling surface 40a, the front wall surface 40b, the side wall surface 40c, and the floor surface 40d are set in the luminance image 20.
  • the brightness feeling prediction unit 28 predicts the brightness feeling of the target space represented by the luminance image 20. It is known that the sense of brightness felt by humans with respect to the target space is proportional to the logarithm of the brightness of each part of the target space. Therefore, the brightness feeling prediction unit 28 basically uses the brightness feeling of the target space as a numerical value based on the geometric mean brightness value which is the geometric mean value of the brightness values of the plurality of pixels constituting the luminance image 20. Predict. Since various methods have been conventionally proposed for calculating the predicted value of the feeling of brightness, detailed description thereof will be omitted here.
  • the brightness feeling prediction unit 28 has the brightness of the pixel corresponding to the light source. Not used to predict the feeling. Specifically, the brightness prediction unit 28 considers a pixel having a brightness value of a predetermined value or more as a pixel corresponding to a light source, and the brightness is based on the geometric mean value of the brightness values of other pixels excluding the pixel. Predict the feeling.
  • the brightness prediction unit 28 refers to the weight information 22, and is a representative value (for example, geometric average) of the luminance values of a plurality of pixels included in each image area 40 set by the surface type setting unit 26.
  • the brightness feeling of the target space represented by the luminance image 20 is predicted based on the luminance value (hereinafter referred to as “luminance representative value”) and the weight of each surface type of the image region 40.
  • the brightness feeling prediction unit 28 changes the degree of influence of the brightness representative value of each image area 40 on the brightness feeling of the target space according to the weight of each surface type indicated by the weight information 22. , Predict the feeling of brightness in the target area. In an extreme example, when there is an image region 40 having a weight of 0, the brightness feeling prediction unit 28 predicts the brightness feeling of the target space by ignoring the brightness representative value of the image region 40.
  • the brightness feeling prediction unit 28 first obtains a luminance representative value of the image domain 40, for example, a geometric mean luminance value for each image domain 40.
  • a luminance representative value of the image region 40 having a larger weight is more important, in other words, the luminance representative value of the image region 40 having a smaller weight is more neglected to predict the brightness feeling of the target space.
  • the weight information 22 is as shown in FIG. 3, since the weight of the front wall surface 40b is large, when the brightness representative value of the front wall surface 40b is large, the feeling of brightness of the target space becomes large (feels bright). ), And when the representative brightness value of the front wall surface 40b is small, it acts greatly in the direction in which the feeling of brightness of the target space becomes small (feels dark). On the other hand, since the weight of the floor surface 40d is small, even when the brightness representative value of the floor surface 40d is large, it does not act much in the direction of increasing the brightness feeling of the target space, and the brightness representative of the floor surface 40d. Even if the value is small, it does not work so much in the direction that the feeling of brightness of the target space becomes small.
  • the brightness prediction unit 28 has a luminance representative value of the first image region 40 in the luminance image 20 and a luminance representative value of the second image region 40 located in the vicinity of the first image region 40 in the luminance image 20. It is preferable to predict the feeling of brightness of the target space based on the ratio of.
  • the second image area 40 located in the vicinity of the first image area 40 is typically an image area 40 adjacent to the first image area 40, but is located in the vicinity of the first image area 40. If so, the second image area 40 does not necessarily have to be adjacent to the first image area 40.
  • the inventor of the present invention feels that in the luminance image 20, the larger the ratio of the luminance representative values of the two image regions 40 in the vicinity is, the darker the human being is with respect to the target space, that is, the smaller the sense of brightness. I found that.
  • the large ratio of the luminance representative values of the two image regions 40 means that the difference between the luminance representative values of the two image regions 40 is large.
  • FIG. 2 for example, when the ratio of the brightness representative value between the central ceiling surface and the side wall adjacent to the central ceiling surface is large, the ratio of the brightness representative value between the ceiling surface and the side wall is large. Compared to the case where is small, humans feel that the target space is dark.
  • the brightness feeling prediction unit 28 has, for each image area 40 (each first image area 40) included in the luminance image 20, with each of the other plurality of image areas 40 (second image area 40) in the vicinity thereof. Calculate the ratio of the representative brightness values between. Then, the feeling of brightness of the target space is predicted in consideration of the sum or average value of the calculated plurality of ratios. Specifically, the larger the total or average value of the calculated multiple ratios, the smaller the brightness of the target space, and the smaller the total or average value of the calculated multiple ratios, the smaller the brightness of the target space. Enlarge.
  • the floor surface 40d tends to have a considerably low representative brightness value. Therefore, even if a human feels relatively bright with respect to the target space, the image area 40 corresponding to the floor surface 40d and another image area 40 in the vicinity thereof (for example, the front wall surface 40b or the side wall surface 40c)
  • the ratio of the representative luminance value to the image region 40) corresponding to the above tends to be large. Therefore, when calculating the ratio of the representative luminance values between the two image regions 40, it is preferable that the brightness prediction unit 28 does not consider the image region 40 corresponding to the floor surface 40d set by the surface type setting unit 26. Is. In other words, the brightness prediction unit 28 does not consider the ratio between the luminance representative value of the image region 40 corresponding to the floor surface 40d and the luminance representative value of the other image region 40, and the brightness of the target space. It is preferable to predict the feeling.
  • the brightness feeling prediction unit 28 intermittently predicts the brightness feeling of the same target space at a plurality of different times. For example, the brightness prediction unit 28 periodically predicts the brightness of the target space, such as every 30 minutes or every 5 minutes. This is because the feeling of brightness of the target space may change depending on the time of day. For example, since sunlight is the light source in the daytime, the position of the sun changes depending on the time of day, which changes the way the light hits the target space and the feeling of brightness may change. Moreover, since the main light source is a lighting fixture at night, the feeling of brightness in the same target space may be completely different from that in the daytime.
  • the brightness feeling prediction unit 28 intermittently predicts the brightness feeling of the target space based on the plurality of luminance images 20 that are intermittently acquired. For example, a camera that captures an image of a certain target space is fixedly installed, and the camera intermittently photographs the target space to acquire a plurality of camera images.
  • the plurality of camera images may be a plurality of luminance images 20, and a plurality of luminance expanded images processed to expand the luminance range of each camera image may be a plurality of luminance images 20.
  • the feeling of brightness prediction unit 28 may predict the feeling of brightness of the target space in consideration of the above-mentioned dark adaptation or light adaptation. Specifically, the brightness prediction unit 28 predicts the brightness of the target space this time based on the difference between the brightness feeling of the target space predicted immediately before and the brightness feeling of the target space predicted this time. You may try to correct the feeling.
  • the brightness prediction unit 28 increases the difference between the brightness feeling of the target space predicted immediately before and the brightness feeling of the target space predicted this time, the larger the difference is, the brightness of the target space predicted this time. Correct so that the feeling of touch is reduced. In other words, the brightness prediction unit 28 has the smaller the difference between the brightness feeling of the target space predicted immediately before and the brightness feeling of the target space predicted this time, the smaller the difference is, the more the target space predicted this time. Correct so that the feeling of brightness becomes large.
  • the brightness feeling prediction unit 28 predicts immediately before the case where the brightness feeling of the target space predicted immediately before is 6, that is, the difference in the brightness feeling is 1.
  • the brightness feeling of the target space is 12, that is, when the difference in brightness feeling is 7, that is, when the difference is large, the correction is made so that the predicted value of the brightness feeling this time becomes smaller. do.
  • the brightness feeling prediction unit 28 predicts immediately before the case where the brightness feeling of the target space predicted immediately before is 14, that is, the difference in the brightness feeling is -1.
  • the brightness feeling of the target space is 9, that is, when the difference in brightness feeling is -6, that is, when the difference is small, the predicted value of the brightness feeling this time becomes larger. Make corrections.
  • the outline of the configuration of the brightness feeling prediction device 10 according to the present embodiment is as described above.
  • weights are set according to a plurality of surface types defined in the brightness image 20, and the weights are taken into consideration to give a feeling of brightness in the target space based on the brightness image 20. is expected.
  • it is possible to predict the feeling of brightness with higher accuracy that is, the feeling of brightness closer to the actual feeling of human beings, as compared with the case where the feeling of brightness is predicted at least without considering the surface type included in the luminance image 20.
  • Brightness prediction device 10 Brightness prediction device, 12 Communication unit, 14 Display unit, 16 Input unit, 18 Storage unit, 20 Brightness image, 22 Weight information, 24 Control unit, 26 Surface type setting unit, 28 Brightness prediction unit, 40 Image Area, 40a ceiling surface, 40b front wall surface, 40c side wall surface, 40d floor surface.

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Abstract

According to the present invention, a surface type setting unit (26) defines each image area corresponding to each surface included in a luminance image (20) representing a target space, and sets surface types of the defined plurality of image areas. A brightness feeling prediction unit (28) refers to weight information (22) in which weight indicating a degree of contribution to brightness feeling is associated with each surface type that can be defined in the luminance image (20), and predicts the brightness feeling of the target space represented by the luminance image (20), on the basis of a representative value of the brightness values of a plurality of pixels included in each image area (40) set by the surface type setting unit (26) and the weight of the surface type of each image area (40).

Description

明るさ感予測装置及び明るさ感予測プログラムBrightness prediction device and brightness prediction program
　本発明は、明るさ感予測装置及び明るさ感予測プログラムに関する。 The present invention relates to a brightness feeling prediction device and a brightness feeling prediction program.
　近年、人間が空間に対して感じる明るさ量を示す明るさ感という指標が提案されている。明るさ感とは、あくまで人間が感じる明るさ量であり、物体の表面を照らす光の明るさを表す物理量である照度などとは異なる指標である。したがって、例えば空間に設置されている照明の照度が大きかったとしても、必ずしも当該空間に対する明るさ感が大きくなるとは限らない。 In recent years, an index called a sense of brightness, which indicates the amount of brightness that humans perceive in space, has been proposed. The sense of brightness is the amount of brightness that humans perceive, and is an index different from the illuminance, which is a physical quantity that represents the brightness of light that illuminates the surface of an object. Therefore, for example, even if the illuminance of the lighting installed in the space is large, the feeling of brightness for the space is not always large.
　従来、空間に対する明るさ感を予測する装置あるいはプログラムが提案されている。例えば、特許文献１には、明るさ感を予測する対象である対象空間を撮像した画像に含まれる各画素の輝度に基づいて、当該空間の明るさ感を予測する明るさ感予測装置が開示されている。また、特許文献２には、対象空間内の鉛直面上の点における照度に基づいて、当該空間の明るさ感を予測する明るさ感予測装置が開示されている。 Conventionally, devices or programs that predict the feeling of brightness in space have been proposed. For example, Patent Document 1 discloses a brightness feeling predicting device that predicts the brightness feeling of the space based on the brightness of each pixel included in the image of the target space that is the object for predicting the brightness feeling. Has been done. Further, Patent Document 2 discloses a brightness feeling predicting device that predicts the brightness feeling of the space based on the illuminance at a point on a vertical surface in the target space.
特許第３９９５２０１号公報Japanese Patent No. 3995201 国際公開第２０１２／０４６８４０号パンフレットInternational Publication No. 2012/046840 Pamphlet
　従来、装置あるいはプログラムによって対象空間の明るさ感を予測するに当たり、実際に人間が当該対象空間から感じた明るさ感とは異なる明るさ感が予測されてしまう場合があった。すなわち、対象空間に対する明るさ感の予測が適切に行えない場合があった。 Conventionally, when predicting the feeling of brightness of the target space by a device or a program, there was a case where a feeling of brightness different from the feeling of brightness actually felt by a human being from the target space was predicted. That is, there are cases where it is not possible to properly predict the feeling of brightness with respect to the target space.
　本発明の目的は、対象空間の明るさ感を高精度に予測することにある。 An object of the present invention is to predict the brightness of the target space with high accuracy.
　本発明は、対象空間を表す輝度画像に含まれる各面に対応する各画像領域の面種別を設定する面種別設定部と、各面種別に対して明るさ感への寄与度を示す重みが関連付けられた重み情報を参照し、複数の前記画像領域それぞれについての、当該画像領域に含まれる複数の画素の輝度値及び当該画像領域の面種別の重みに基づいて、前記対象空間の明るさ感を予測する明るさ感予測部と、を備えることを特徴とする明るさ感予測装置である。 In the present invention, the surface type setting unit that sets the surface type of each image area corresponding to each surface included in the luminance image representing the target space, and the weight indicating the degree of contribution to the feeling of brightness for each surface type are used. With reference to the associated weight information, the brightness feeling of the target space is based on the luminance values of the plurality of pixels included in the image region and the weights of the surface types of the image region for each of the plurality of image regions. It is a brightness feeling prediction device characterized by including a brightness feeling prediction unit for predicting.
　望ましくは、前記明るさ感予測部は、前記複数の画像領域のうち、第１画像領域に含まれる複数の画素の輝度値の代表値と、前記輝度画像において前記第１画像領域の近傍に位置する第２画像領域に含まれる複数の画素の輝度値の代表値との比にさらに基づいて、前記対象空間の明るさ感を予測する、ことを特徴とする。 Desirably, the brightness prediction unit is located in the vicinity of the representative value of the luminance values of the plurality of pixels included in the first image region and the vicinity of the first image region in the luminance image among the plurality of image regions. It is characterized in that the feeling of brightness of the target space is predicted based on the ratio of the luminance values of the plurality of pixels included in the second image region to the representative values.
　望ましくは、前記明るさ感予測部は、前記複数の画像領域のうち面種別が床面である画像領域に含まれる複数の画素の輝度値の代表値と、他の画像領域に含まれる複数の画素の輝度値の代表値との比は考慮せずに、前記対象空間の明るさ感を予測する、ことを特徴とする。 Desirably, the brightness prediction unit includes a representative value of the luminance values of a plurality of pixels included in the image region whose surface type is the floor surface among the plurality of image regions, and a plurality of brightness values included in the other image regions. It is characterized in that the feeling of brightness of the target space is predicted without considering the ratio of the brightness value of the pixel to the representative value.
　望ましくは、前記明るさ感予測部は、間欠的に前記対象空間の明るさ感を予測し、直前に予測された前記対象空間の明るさ感と、今回予測した前記対象空間の明るさ感との差分に基づいて、今回予測した前記対象空間の明るさ感を補正する、ことを特徴とする。 Desirably, the brightness feeling predicting unit intermittently predicts the brightness feeling of the target space, and the brightness feeling of the target space predicted immediately before and the brightness feeling of the target space predicted this time. It is characterized in that the brightness feeling of the target space predicted this time is corrected based on the difference between the above.
　また、本発明は、コンピュータを、対象空間を表す輝度画像に含まれる各面に対応する各画像領域の面種別を設定する面種別設定部と、各面種別に対して明るさ感への寄与度を示す重みが関連付けられた重み情報を参照し、複数の前記画像領域それぞれについての、当該画像領域に含まれる複数の画素の輝度値及び当該画像領域の面種別の重みに基づいて、前記対象空間の明るさ感を予測する明るさ感予測部と、として機能させることを特徴とする明るさ感予測プログラムである。 Further, the present invention comprises a surface type setting unit for setting a surface type of each image area corresponding to each surface included in a luminance image representing a target space, and a contribution to a sense of brightness for each surface type. With reference to the weight information associated with the weight indicating the degree, the target is based on the brightness values of the plurality of pixels included in the image region and the weight of the surface type of the image region for each of the plurality of image regions. It is a brightness prediction program characterized by functioning as a brightness prediction unit that predicts the brightness of a space.
　本発明によれば、対象空間の明るさ感を高精度に予測することができる。 According to the present invention, the feeling of brightness of the target space can be predicted with high accuracy.
本実施形態に係る明るさ感予測装置の構成概略図である。It is a block diagram of the brightness feeling prediction apparatus which concerns on this embodiment. 輝度画像の例を示す図である。It is a figure which shows the example of the luminance image. 重み情報の例を示す概念図である。It is a conceptual diagram which shows an example of weight information. 輝度画像において定義された画像領域を示す図である。It is a figure which shows the image area defined in the luminance image.
　図１は、本実施形態に係る明るさ感予測装置１０の構成概略図である。明るさ感予測装置１０は、例えばサーバコンピュータ、パーソナルコンピュータ、あるいはタブレット端末などであるが、以下に説明する機能を発揮可能な限りにおいてどのような装置であってもよい。また、本実施形態に係る明るさ感予測装置１０は、以下に説明する各機能を１つの装置で発揮するが、複数の装置によって明るさ感予測装置１０の各機能が発揮されてもよい。 FIG. 1 is a schematic configuration diagram of the brightness feeling prediction device 10 according to the present embodiment. The brightness feeling prediction device 10 is, for example, a server computer, a personal computer, a tablet terminal, or the like, but may be any device as long as the functions described below can be exhibited. Further, although the brightness feeling prediction device 10 according to the present embodiment exerts each function described below in one device, each function of the brightness feeling prediction device 10 may be exerted by a plurality of devices.
　通信部１２は、例えばネットワークアダプタなどを含んで構成される。通信部１２は、ＬＡＮやインターネットなどの通信回線を介して、他の装置（例えばカメラや、カメラで撮像した画像を処理する画像処理装置など）と通信する機能を発揮する。例えば、通信部１２は、後述の輝度画像２０を他の装置から受信する。また、通信部１２は、後述の明るさ感予測部２８による予測結果を他の装置に送信してもよい。 The communication unit 12 is configured to include, for example, a network adapter. The communication unit 12 exhibits a function of communicating with another device (for example, a camera or an image processing device that processes an image captured by the camera) via a communication line such as a LAN or the Internet. For example, the communication unit 12 receives the luminance image 20 described later from another device. Further, the communication unit 12 may transmit the prediction result by the brightness feeling prediction unit 28, which will be described later, to another device.
　表示部１４は、例えば液晶ディスプレイや有機ＥＬディスプレイなどを含んで構成される。表示部１４は、種々の画面を表示する。例えば、表示部１４は、輝度画像２０や、明るさ感予測部２８による予測結果を表示可能である。 The display unit 14 includes, for example, a liquid crystal display, an organic EL display, and the like. The display unit 14 displays various screens. For example, the display unit 14 can display the luminance image 20 and the prediction result by the brightness feeling prediction unit 28.
　入力部１６は、例えばマウス、キーボード、タッチパネル、マイクなどを含んで構成される。入力部１６は、ユーザからの指示を明るさ感予測装置１０に入力するために用いられる。 The input unit 16 includes, for example, a mouse, a keyboard, a touch panel, a microphone, and the like. The input unit 16 is used to input an instruction from the user to the brightness feeling prediction device 10.
　記憶部１８は、例えばハードディスク、ＳＳＤ、ＲＯＭ、あるいはＲＡＭなどを含んで構成される。記憶部１８には、明るさ感予測装置１０の各部を動作させるための明るさ感予測プログラムが記憶される。また、図１に示す通り、記憶部１８には、輝度画像２０及び重み情報２２が記憶される。 The storage unit 18 includes, for example, a hard disk, SSD, ROM, RAM, or the like. The storage unit 18 stores a brightness prediction program for operating each unit of the brightness prediction device 10. Further, as shown in FIG. 1, the luminance image 20 and the weight information 22 are stored in the storage unit 18.
　輝度画像２０は、明るさ感予測装置１０によって明るさ感を予測する対象となる空間である対象空間を表す画像である。本明細書における対象空間とは、複数種類の面（例えば壁面、天井面、床面など）を含む空間である。例えば、対象空間は屋内の空間である。 The brightness image 20 is an image representing a target space, which is a space for which a brightness feeling is predicted by the brightness feeling prediction device 10. The target space in the present specification is a space including a plurality of types of surfaces (for example, a wall surface, a ceiling surface, a floor surface, etc.). For example, the target space is an indoor space.
　図２に、輝度画像２０の例が示されている。輝度画像２０は、複数の画素が２次元配列されたものである。輝度画像２０に含まれる各画素は、画素値として少なくとも輝度値を有していればよい。輝度画像２０は、対象空間をカメラで撮影して得られたカメラ画像であってよい。また、カメラ画像は各画素の輝度値のレンジ（範囲）が比較的狭い（例えば０～２５５）ところ、輝度画像２０は、カメラ画像の各画素の輝度のレンジを拡張する処理が施された輝度拡張画像であるのが好適である。なお、輝度画像２０としては、カメラ画像に基づく画像ではなく、コンピュータプログラムによって形成された画像、例えばＣＧ画像などであってもよい。明るさ感予測装置１０は、上述の通信部１２により他の装置から輝度画像２０を受信して記憶部１８に記憶させる。あるいは、明るさ感予測装置１０が輝度画像２０を形成してもよい。 FIG. 2 shows an example of the luminance image 20. The luminance image 20 is a two-dimensional array of a plurality of pixels. Each pixel included in the luminance image 20 may have at least a luminance value as a pixel value. The luminance image 20 may be a camera image obtained by photographing the target space with a camera. Further, in the camera image, the range (range) of the brightness value of each pixel is relatively narrow (for example, 0 to 255), whereas in the brightness image 20, the luminance is processed to expand the luminance range of each pixel of the camera image. It is preferable that it is an extended image. The luminance image 20 may be an image formed by a computer program, for example, a CG image, instead of an image based on a camera image. The brightness feeling prediction device 10 receives the luminance image 20 from another device by the communication unit 12 described above and stores it in the storage unit 18. Alternatively, the brightness feeling prediction device 10 may form the luminance image 20.
　図１に戻り、重み情報２２は、輝度画像２０内において定義され得る各面種別に対して、明るさ感への寄与度を示す重みが関連付けられた情報である。上述のように、対象空間には複数種類の面が含まれているところ、本願発明の発明者は、アンケートなどの調査結果に基づいて、対象空間に含まれている面種別に応じて、面に含まれる各画素の輝度値が当該対象空間についての明るさ感に与える影響、すなわち明るさ感への寄与度が異なることを見出した。したがって、当該調査結果に基づく、各面種別に対する明るさ感への寄与度を示す重みが、重み情報２２として予め記憶部１８に記憶される。 Returning to FIG. 1, the weight information 22 is information in which a weight indicating the degree of contribution to the feeling of brightness is associated with each surface type that can be defined in the luminance image 20. As described above, the target space includes a plurality of types of surfaces, but the inventor of the present invention has a surface according to the surface type included in the target space based on the results of a survey such as a questionnaire. It was found that the influence of the brightness value of each pixel included in the above on the feeling of brightness of the target space, that is, the degree of contribution to the feeling of brightness is different. Therefore, the weight indicating the degree of contribution to the feeling of brightness for each surface type based on the survey result is stored in the storage unit 18 in advance as the weight information 22.
　図３に重み情報２２の例が示されている。図３には、面種別として、天井面、正面壁面、側壁面、及び床面が示されている。天井面とは対象空間の天井に対応する面であり、正面壁面とは、輝度画像２０の視野内において輝度画像２０の左右方向に延伸する壁に対応する面であり、側壁面とは、輝度画像２０の視野内において、奥行方向に延伸する壁に対応する面であり、床面とは対象空間の床に対応する面である。もちろん、面種別としてはこれらに限られず、他の種類の面（例えば窓面など）が含まれていてもよい。 FIG. 3 shows an example of the weight information 22. FIG. 3 shows a ceiling surface, a front wall surface, a side wall surface, and a floor surface as surface types. The ceiling surface is a surface corresponding to the ceiling of the target space, the front wall surface is a surface corresponding to the wall extending in the left-right direction of the brightness image 20 in the field of view of the brightness image 20, and the side wall surface is the surface corresponding to the brightness. In the field of view of the image 20, the surface corresponding to the wall extending in the depth direction, and the floor surface is the surface corresponding to the floor of the target space. Of course, the surface type is not limited to these, and other types of surfaces (for example, window surfaces) may be included.
　図３に示した４つの面種別のうち、対象空間についての明るさ感への寄与度は、大きい方から、正面壁面、天井面、側壁面、床面の順であることを本願発明の発明者は見出した。したがって、当該４つの面種別のうち、正面壁面の重みが最も大きく、天井面の重みが次に大きく、側壁面の重みが次に大きく、床面の重みが一番小さくなっている。重みの実際の値は例であり、明るさ感の算出のための式などに応じて適宜変更されてよい。 Of the four surface types shown in FIG. 3, the invention of the present invention states that the degree of contribution to the sense of brightness of the target space is in the order of front wall surface, ceiling surface, side wall surface, and floor surface from the largest. Found. Therefore, among the four surface types, the weight of the front wall surface is the largest, the weight of the ceiling surface is the next largest, the weight of the side wall surface is the next largest, and the weight of the floor surface is the smallest. The actual value of the weight is an example, and may be appropriately changed according to an equation for calculating the feeling of brightness.
　図１に戻り、制御部２４は、例えばＣＰＵ、ＧＰＵ、ＡＳＩＣ、ＦＰＧＡなどの各種制御装置などを含んで構成される。制御部２４は、記憶部１８に記憶された明るさ感予測プログラムに基づいて、明るさ感予測装置１０の各部を制御する。特に、図１に示すように、制御部２４は、面種別設定部２６及び明るさ感予測部２８としての機能を発揮する。 Returning to FIG. 1, the control unit 24 includes, for example, various control devices such as a CPU, GPU, ASIC, and FPGA. The control unit 24 controls each unit of the brightness sensation prediction device 10 based on the brightness sensation prediction program stored in the storage unit 18. In particular, as shown in FIG. 1, the control unit 24 functions as a surface type setting unit 26 and a brightness feeling prediction unit 28.
　面種別設定部２６は、まず、輝度画像２０内に含まれる各面に対応する各画像領域を定義する。本実施形態では、面種別設定部２６は、輝度画像２０に対する画像解析を施すことで複数の画像領域を定義する。具体的には、面種別設定部２６は輝度画像２０に対してエッジ検出処理を施し、検出したエッジで囲われた領域、あるいは、検出したエッジと輝度画像２０の辺によって囲われた領域を１つの画像領域として定義する。なお、このとき、所定面積（画素数）以下の領域は画像領域としては定義せずに無視するようにしてもよい。これにより、輝度画像２０に含まれる面以外のオブジェクト（例えば家具や柱など）を除外することができる。また、面種別設定部２６は、輝度画像２０に対する画像処理を行わず、ユーザからの指示に従って輝度画像２０内において複数の画像領域を定義するようにしてもよい。 The surface type setting unit 26 first defines each image area corresponding to each surface included in the luminance image 20. In the present embodiment, the surface type setting unit 26 defines a plurality of image regions by performing image analysis on the luminance image 20. Specifically, the surface type setting unit 26 performs edge detection processing on the luminance image 20, and sets the region surrounded by the detected edge or the region surrounded by the detected edge and the side of the luminance image 20 as 1. Defined as one image area. At this time, the area below the predetermined area (number of pixels) may be ignored without being defined as an image area. As a result, objects other than the surface included in the luminance image 20 (for example, furniture, pillars, etc.) can be excluded. Further, the surface type setting unit 26 may define a plurality of image areas in the luminance image 20 according to an instruction from the user without performing image processing on the luminance image 20.
　次いで、面種別設定部２６は、定義した複数の画像領域の面種別を設定する。本実施形態では、面種別設定部２６は、定義した画像領域の形状や輝度画像２０内における位置に基づいて、その面種別を設定する。例えば、面種別設定部２６は、台形の画像領域であって、上底と下底とが平行であり、下底よりも上底の方が長く、輝度画像２０内の上側に位置する画像領域の面種別を天井面と設定する。また、面種別設定部２６は、四角形の画像領域であって、左右側の少なくとも一方の辺が垂直である（輝度画像２０において上下方向に延伸している）画像領域の面種別を側壁面と設定する。また、面種別設定部２６は、定義した画像領域の形状や輝度画像２０内における位置に依らず、ユーザからの指示に従って各画像領域の面種別を特定するようにしてもよい。 Next, the surface type setting unit 26 sets the surface types of a plurality of defined image areas. In the present embodiment, the surface type setting unit 26 sets the surface type based on the shape of the defined image area and the position in the luminance image 20. For example, the surface type setting unit 26 is a trapezoidal image region in which the upper base and the lower base are parallel to each other, the upper base is longer than the lower base, and the image region is located on the upper side in the luminance image 20. Set the surface type of to ceiling surface. Further, the surface type setting unit 26 is a quadrangular image region, and the surface type of the image region in which at least one side on the left and right sides is vertical (extended in the vertical direction in the luminance image 20) is referred to as a side wall surface. Set. Further, the surface type setting unit 26 may specify the surface type of each image area according to an instruction from the user, regardless of the shape of the defined image area or the position in the luminance image 20.
　図４に、図２に示した輝度画像２０において定義された複数の画像領域４０と各画像領域４０の面種別が示されている。図４においては、輝度画像２０内において、天井面４０ａ、正面壁面４０ｂ、側壁面４０ｃ、及び床面４０ｄが設定されている。 FIG. 4 shows a plurality of image regions 40 defined in the luminance image 20 shown in FIG. 2 and surface types of each image region 40. In FIG. 4, the ceiling surface 40a, the front wall surface 40b, the side wall surface 40c, and the floor surface 40d are set in the luminance image 20.
　明るさ感予測部２８は、輝度画像２０が表す対象空間の明るさ感を予測する。対象空間に対する人間が感じる明るさ感は、対象空間の各部の輝度の対数に比例することが知られている。したがって、明るさ感予測部２８は、基本的には、輝度画像２０を構成する複数の画素の輝度値の幾何平均値である幾何平均輝度値に基づいて、対象空間の明るさ感を数値として予測する。明るさ感の予測値を算出するための式は、従来種々の方式が提案されているためここでは詳細な説明は省略する。なお、輝度画像２０内に含まれる光源（例えば電球など）は、明るさ感に与える影響がかなり小さいことが知られているため、明るさ感予測部２８は、光源に対応する画素は明るさ感の予測に用いない。具体的には、明るさ感予測部２８は、輝度値が所定値以上の画素は光源に対応する画素とみなし、当該画素を除いた他の画素の輝度値の幾何平均値に基づいて明るさ感の予測を行う。 The brightness feeling prediction unit 28 predicts the brightness feeling of the target space represented by the luminance image 20. It is known that the sense of brightness felt by humans with respect to the target space is proportional to the logarithm of the brightness of each part of the target space. Therefore, the brightness feeling prediction unit 28 basically uses the brightness feeling of the target space as a numerical value based on the geometric mean brightness value which is the geometric mean value of the brightness values of the plurality of pixels constituting the luminance image 20. Predict. Since various methods have been conventionally proposed for calculating the predicted value of the feeling of brightness, detailed description thereof will be omitted here. Since it is known that the light source (for example, a light bulb) included in the luminance image 20 has a considerably small influence on the brightness feeling, the brightness feeling prediction unit 28 has the brightness of the pixel corresponding to the light source. Not used to predict the feeling. Specifically, the brightness prediction unit 28 considers a pixel having a brightness value of a predetermined value or more as a pixel corresponding to a light source, and the brightness is based on the geometric mean value of the brightness values of other pixels excluding the pixel. Predict the feeling.
　特に、本実施形態では、明るさ感予測部２８は、重み情報２２を参照し、面種別設定部２６が設定した各画像領域４０に含まれる複数の画素の輝度値の代表値（例えば幾何平均輝度値、以下「輝度代表値」と記載する）と、各画像領域４０の面種別の重みに基づいて、輝度画像２０が表す対象空間の明るさ感を予測する。具体的には、明るさ感予測部２８は、重み情報２２が示す各面種別の重みに応じて、対象空間の明るさ感に与える、各画像領域４０の輝度代表値の影響度を変えながら、対象領域の明るさ感を予測する。極端な例では、重みが０の画像領域４０がある場合、明るさ感予測部２８は、当該画像領域４０の輝度代表値を無視して対象空間の明るさ感を予測する。 In particular, in the present embodiment, the brightness prediction unit 28 refers to the weight information 22, and is a representative value (for example, geometric average) of the luminance values of a plurality of pixels included in each image area 40 set by the surface type setting unit 26. The brightness feeling of the target space represented by the luminance image 20 is predicted based on the luminance value (hereinafter referred to as “luminance representative value”) and the weight of each surface type of the image region 40. Specifically, the brightness feeling prediction unit 28 changes the degree of influence of the brightness representative value of each image area 40 on the brightness feeling of the target space according to the weight of each surface type indicated by the weight information 22. , Predict the feeling of brightness in the target area. In an extreme example, when there is an image region 40 having a weight of 0, the brightness feeling prediction unit 28 predicts the brightness feeling of the target space by ignoring the brightness representative value of the image region 40.
　その手法はいろいろな手法を採用することができるが、その一例として、明るさ感予測部２８は、まず、画像領域４０毎に、画像領域４０の輝度代表値、例えば幾何平均輝度値を求める。その上で、重みがより大きい画像領域４０の輝度代表値をより重視し、換言すれば重みがより小さい画像領域４０の輝度代表値をより軽視して対象空間の明るさ感を予測する。 Various methods can be adopted as the method, but as an example, the brightness feeling prediction unit 28 first obtains a luminance representative value of the image domain 40, for example, a geometric mean luminance value for each image domain 40. On top of that, the luminance representative value of the image region 40 having a larger weight is more important, in other words, the luminance representative value of the image region 40 having a smaller weight is more neglected to predict the brightness feeling of the target space.
　例えば、重み情報２２が図３に示す通りであるとすると、正面壁面４０ｂの重みが大きいため、正面壁面４０ｂの輝度代表値が大きい場合は、対象空間の明るさ感が大きくなる（明るいと感じる）方向に大きく作用し、また、正面壁面４０ｂの輝度代表値が小さい場合は、対象空間の明るさ感が小さくなる（暗いと感じる）方向に大きく作用する。一方、床面４０ｄの重みが小さいため、床面４０ｄの輝度代表値が大きい場合であっても、対象空間の明るさ感が大きくなる方向にあまり作用せず、また、床面４０ｄの輝度代表値が小さい場合であっても、対象空間の明るさ感が小さくなる方向にあまり作用しない。 For example, assuming that the weight information 22 is as shown in FIG. 3, since the weight of the front wall surface 40b is large, when the brightness representative value of the front wall surface 40b is large, the feeling of brightness of the target space becomes large (feels bright). ), And when the representative brightness value of the front wall surface 40b is small, it acts greatly in the direction in which the feeling of brightness of the target space becomes small (feels dark). On the other hand, since the weight of the floor surface 40d is small, even when the brightness representative value of the floor surface 40d is large, it does not act much in the direction of increasing the brightness feeling of the target space, and the brightness representative of the floor surface 40d. Even if the value is small, it does not work so much in the direction that the feeling of brightness of the target space becomes small.
　また、明るさ感予測部２８は、輝度画像２０内の第１画像領域４０の輝度代表値と、輝度画像２０において第１画像領域４０の近傍に位置する第２画像領域４０の輝度代表値との比にさらに基づいて、対象空間の明るさ感を予測するのが好適である。ここで、第１画像領域４０の近傍に位置する第２画像領域４０とは、代表的には第１画像領域４０に隣接する画像領域４０であるが、第１画像領域４０の近傍に位置していれば、第２画像領域４０は必ずしも第１画像領域４０に隣接していなくてもよい。 Further, the brightness prediction unit 28 has a luminance representative value of the first image region 40 in the luminance image 20 and a luminance representative value of the second image region 40 located in the vicinity of the first image region 40 in the luminance image 20. It is preferable to predict the feeling of brightness of the target space based on the ratio of. Here, the second image area 40 located in the vicinity of the first image area 40 is typically an image area 40 adjacent to the first image area 40, but is located in the vicinity of the first image area 40. If so, the second image area 40 does not necessarily have to be adjacent to the first image area 40.
　本願発明の発明者は、輝度画像２０において、近傍にある２つの画像領域４０の輝度代表値の比が大きい程、人間は、対象空間に対して暗いと感じる、すなわち明るさ感が小さいと感じることを見出した。なお、２つの画像領域４０の輝度代表値の比が大きいとは、両画像領域４０の輝度代表値の差が大きいことを意味する。図２を参照して、例えば、中央の天井面と、その側方に隣接する側壁との間の輝度代表値の比が大きいと、当該天井面と当該側壁との間の輝度代表値の比が小さい場合に比して、人間は、対象空間が暗いと感じる。 The inventor of the present invention feels that in the luminance image 20, the larger the ratio of the luminance representative values of the two image regions 40 in the vicinity is, the darker the human being is with respect to the target space, that is, the smaller the sense of brightness. I found that. The large ratio of the luminance representative values of the two image regions 40 means that the difference between the luminance representative values of the two image regions 40 is large. With reference to FIG. 2, for example, when the ratio of the brightness representative value between the central ceiling surface and the side wall adjacent to the central ceiling surface is large, the ratio of the brightness representative value between the ceiling surface and the side wall is large. Compared to the case where is small, humans feel that the target space is dark.
　したがって、明るさ感予測部２８は、輝度画像２０に含まれる各画像領域４０（各第１画像領域４０）について、その近傍にある他の複数の画像領域４０（第２画像領域４０）それぞれとの間における輝度代表値の比を算出する。そして、算出された複数の比の合計あるいは平均値を考慮して対象空間の明るさ感を予測する。具体的には、算出された複数の比の合計あるいは平均値が大きい程、対象空間の明るさを小さくし、算出された複数の比の合計あるいは平均値が小さい程、対象空間の明るさを大きくする。 Therefore, the brightness feeling prediction unit 28 has, for each image area 40 (each first image area 40) included in the luminance image 20, with each of the other plurality of image areas 40 (second image area 40) in the vicinity thereof. Calculate the ratio of the representative brightness values between. Then, the feeling of brightness of the target space is predicted in consideration of the sum or average value of the calculated plurality of ratios. Specifically, the larger the total or average value of the calculated multiple ratios, the smaller the brightness of the target space, and the smaller the total or average value of the calculated multiple ratios, the smaller the brightness of the target space. Enlarge.
　一般的に、床面４０ｄは代表輝度値がかなり低くなりやすい。したがって、たとえ対象空間に対して人間が比較的明るいと感じる場合であっても、床面４０ｄに対応する画像領域４０と、その近傍にある他の画像領域４０（例えば正面壁面４０ｂや側壁面４０ｃに対応する画像領域４０）との間の代表輝度値の比は、大きくなる傾向にある。したがって、明るさ感予測部２８は、２つの画像領域４０間の代表輝度値の比を算出するに当たり、面種別設定部２６が設定した床面４０ｄに対応する画像領域４０は考慮しないのが好適である。換言すれば、明るさ感予測部２８は、床面４０ｄに対応する画像領域４０の輝度代表値と、他の画像領域４０の輝度代表値との比は考慮せずに、対象空間の明るさ感を予測するのが好適である。 In general, the floor surface 40d tends to have a considerably low representative brightness value. Therefore, even if a human feels relatively bright with respect to the target space, the image area 40 corresponding to the floor surface 40d and another image area 40 in the vicinity thereof (for example, the front wall surface 40b or the side wall surface 40c) The ratio of the representative luminance value to the image region 40) corresponding to the above tends to be large. Therefore, when calculating the ratio of the representative luminance values between the two image regions 40, it is preferable that the brightness prediction unit 28 does not consider the image region 40 corresponding to the floor surface 40d set by the surface type setting unit 26. Is. In other words, the brightness prediction unit 28 does not consider the ratio between the luminance representative value of the image region 40 corresponding to the floor surface 40d and the luminance representative value of the other image region 40, and the brightness of the target space. It is preferable to predict the feeling.
　また、明るさ感予測部２８は、同一の対象空間の明るさ感を間欠的に、換言すれば異なる複数の時刻において予測する。例えば、明るさ感予測部２８は、３０分毎あるいは５分毎など、定期的に対象空間の明るさを予測する。これは、１日の内の時刻によって対象空間の明るさ感が変化する場合があるためである。例えば、昼間においては太陽光が光源となるから、時刻によって太陽の位置が変化し、それにより対象空間に対する光の当たり方が変化して明るさ感が変動し得る。また、夜になれば主な光源は照明器具であるため、同一対象空間における明るさ感は、昼とは全く異なる場合がある。 Further, the brightness feeling prediction unit 28 intermittently predicts the brightness feeling of the same target space at a plurality of different times. For example, the brightness prediction unit 28 periodically predicts the brightness of the target space, such as every 30 minutes or every 5 minutes. This is because the feeling of brightness of the target space may change depending on the time of day. For example, since sunlight is the light source in the daytime, the position of the sun changes depending on the time of day, which changes the way the light hits the target space and the feeling of brightness may change. Moreover, since the main light source is a lighting fixture at night, the feeling of brightness in the same target space may be completely different from that in the daytime.
　明るさ感予測部２８は、間欠的に取得される複数の輝度画像２０に基づいて、対象空間の明るさ感を間欠的に予測する。例えば、ある対象空間を撮像するカメラを固定設置し、当該カメラが対象空間を間欠的に撮影して複数のカメラ画像を取得する。当該複数のカメラ画像を複数の輝度画像２０としてもよいし、各カメラ画像の輝度のレンジを拡張する処理が施された複数の輝度拡張画像を複数の輝度画像２０としてもよい。 The brightness feeling prediction unit 28 intermittently predicts the brightness feeling of the target space based on the plurality of luminance images 20 that are intermittently acquired. For example, a camera that captures an image of a certain target space is fixedly installed, and the camera intermittently photographs the target space to acquire a plurality of camera images. The plurality of camera images may be a plurality of luminance images 20, and a plurality of luminance expanded images processed to expand the luminance range of each camera image may be a plurality of luminance images 20.
　空間が明るい空間から暗い空間へと変化した場合、人間（の眼）は、初めのうちは暗さに慣れておらずかなり周りが見えづらいが、時間経過とともに徐々に眼が慣れてきて周りが見え易くなってくる（暗順応）。また、空間が暗い空間から明るい空間へと変化した場合、人間（の眼）は、初めのうちは明るさに慣れておらずかなり周りが見えづらいが、時間経過とともに徐々に眼が慣れてきて周りが見え易くなってくる（明順応）。 When the space changes from a bright space to a dark space, humans (eyes) are not accustomed to the darkness at first and it is quite difficult to see the surroundings, but as time goes by, the eyes gradually become accustomed to the surroundings. It becomes easier to see (dark adaptation). Also, when the space changes from a dark space to a bright space, humans (eyes) are not accustomed to the brightness at first and it is quite difficult to see the surroundings, but the eyes gradually become accustomed to it over time. It becomes easier to see the surroundings (light adaptation).
　対象空間の明るさ感を間欠的に予測する場合、明るさ感予測部２８は、上述の暗順応又は明順応を考慮して対象空間の明るさ感を予測するようにしてもよい。具体的には、明るさ感予測部２８は、直前に予測された対象空間の明るさ感と、今回予測した対象空間の明るさ感との差分に基づいて、今回予測した対象空間の明るさ感を補正するようにしてもよい。 When predicting the feeling of brightness of the target space intermittently, the feeling of brightness prediction unit 28 may predict the feeling of brightness of the target space in consideration of the above-mentioned dark adaptation or light adaptation. Specifically, the brightness prediction unit 28 predicts the brightness of the target space this time based on the difference between the brightness feeling of the target space predicted immediately before and the brightness feeling of the target space predicted this time. You may try to correct the feeling.
　詳しくは、明るさ感予測部２８は、その直前に予測された当該対象空間の明るさ感から、今回予測した対象空間の明るさ感を差し引いた差が大きい程、今回予測した対象空間の明るさ感が小さくなるように補正する。換言すれば、明るさ感予測部２８は、その直前に予測された当該対象空間の明るさ感から、今回予測した対象空間の明るさ感を差し引いた差が小さい程、今回予測した対象空間の明るさ感が大きくなるように補正する。 Specifically, the brightness prediction unit 28 increases the difference between the brightness feeling of the target space predicted immediately before and the brightness feeling of the target space predicted this time, the larger the difference is, the brightness of the target space predicted this time. Correct so that the feeling of touch is reduced. In other words, the brightness prediction unit 28 has the smaller the difference between the brightness feeling of the target space predicted immediately before and the brightness feeling of the target space predicted this time, the smaller the difference is, the more the target space predicted this time. Correct so that the feeling of brightness becomes large.
　例えば、明るさ感が０～２０までの数値で表現されるとし、今回予測した対象空間の明るさが５である（つまり比較的暗いと予測された）とする。このとき、明るさ感予測部２８は、直前に予測された当該対象空間の明るさ感が６である場合、すなわち、明るさ感の差が１である場合に比して、直前に予測された当該対象空間の明るさ感が１２である場合、すなわち、明るさ感の差が７である場合、つまり差が大きい方が、より今回の明るさ感の予測値が小さくなるように補正をする。 For example, assume that the feeling of brightness is expressed by a numerical value from 0 to 20, and that the brightness of the target space predicted this time is 5 (that is, it is predicted to be relatively dark). At this time, the brightness feeling prediction unit 28 predicts immediately before the case where the brightness feeling of the target space predicted immediately before is 6, that is, the difference in the brightness feeling is 1. When the brightness feeling of the target space is 12, that is, when the difference in brightness feeling is 7, that is, when the difference is large, the correction is made so that the predicted value of the brightness feeling this time becomes smaller. do.
　また、今回予測した対象空間の明るさが１５である（つまり比較的明るいと予測された）とする。このとき、明るさ感予測部２８は、直前に予測された当該対象空間の明るさ感が１４である場合、すなわち、明るさ感の差が－１である場合に比して、直前に予測された当該対象空間の明るさ感が９である場合、すなわち、明るさ感の差が－６である場合、つまり差が小さい方が、より今回の明るさ感の予測値が大きくなるように補正をする。 Also, assume that the brightness of the target space predicted this time is 15 (that is, it is predicted to be relatively bright). At this time, the brightness feeling prediction unit 28 predicts immediately before the case where the brightness feeling of the target space predicted immediately before is 14, that is, the difference in the brightness feeling is -1. When the brightness feeling of the target space is 9, that is, when the difference in brightness feeling is -6, that is, when the difference is small, the predicted value of the brightness feeling this time becomes larger. Make corrections.
　本実施形態に係る明るさ感予測装置１０の構成概要は以上の通りである。明るさ感予測装置１０によれば、輝度画像２０内において定義された複数の面種別に応じて重みが設定され、当該重みが考慮されて、輝度画像２０に基づいて対象空間の明るさ感が予測される。これにより、少なくとも輝度画像２０に含まれる面種別を考慮せずに明るさ感を予測した場合に比して、高精度に、すなわち人間の実感により近い明るさ感を予測することができる。 The outline of the configuration of the brightness feeling prediction device 10 according to the present embodiment is as described above. According to the brightness feeling prediction device 10, weights are set according to a plurality of surface types defined in the brightness image 20, and the weights are taken into consideration to give a feeling of brightness in the target space based on the brightness image 20. is expected. As a result, it is possible to predict the feeling of brightness with higher accuracy, that is, the feeling of brightness closer to the actual feeling of human beings, as compared with the case where the feeling of brightness is predicted at least without considering the surface type included in the luminance image 20.
　以上、本発明に係る実施形態を説明したが、本発明は上記実施形態に限られるものではなく、本発明の趣旨を逸脱しない限りにおいて種々の変更が可能である。 Although the embodiments according to the present invention have been described above, the present invention is not limited to the above embodiments, and various modifications can be made without departing from the spirit of the present invention.
　１０　明るさ感予測装置、１２　通信部、１４　表示部、１６　入力部、１８　記憶部、２０　輝度画像、２２　重み情報、２４　制御部、２６　面種別設定部、２８　明るさ感予測部、４０　画像領域、４０ａ　天井面、４０ｂ　正面壁面、４０ｃ　側壁面、４０ｄ　床面。 10 Brightness prediction device, 12 Communication unit, 14 Display unit, 16 Input unit, 18 Storage unit, 20 Brightness image, 22 Weight information, 24 Control unit, 26 Surface type setting unit, 28 Brightness prediction unit, 40 Image Area, 40a ceiling surface, 40b front wall surface, 40c side wall surface, 40d floor surface.

Claims (5)

  1. 　対象空間を表す輝度画像に含まれる各面に対応する各画像領域の面種別を設定する面種別設定部と、
    　各面種別に対して明るさ感への寄与度を示す重みが関連付けられた重み情報を参照し、複数の前記画像領域それぞれについての、当該画像領域に含まれる複数の画素の輝度値及び当該画像領域の面種別の重みに基づいて、前記対象空間の明るさ感を予測する明るさ感予測部と、
    　を備えることを特徴とする明るさ感予測装置。     A surface type setting unit that sets the surface type of each image area corresponding to each surface included in the luminance image representing the target space, and a surface type setting unit.
    With reference to the weight information associated with the weight indicating the degree of contribution to the feeling of brightness for each surface type, the brightness values of the plurality of pixels included in the image area and the image for each of the plurality of image areas. A brightness prediction unit that predicts the brightness of the target space based on the weight of the surface type of the region,
    A brightness prediction device characterized by being equipped with.
  2. 　前記明るさ感予測部は、前記複数の画像領域のうち、第１画像領域に含まれる複数の画素の輝度値の代表値と、前記輝度画像において前記第１画像領域の近傍に位置する第２画像領域に含まれる複数の画素の輝度値の代表値との比にさらに基づいて、前記対象空間の明るさ感を予測する、
    　ことを特徴とする請求項１に記載の明るさ感予測装置。     The brightness prediction unit has a representative value of the brightness values of a plurality of pixels included in the first image area among the plurality of image areas, and a second image located in the vicinity of the first image area in the brightness image. Further, the brightness feeling of the target space is predicted based on the ratio of the luminance values of the plurality of pixels included in the image region to the representative values.
    The brightness feeling prediction device according to claim 1.
  3. 　前記明るさ感予測部は、前記複数の画像領域のうち面種別が床面である画像領域に含まれる複数の画素の輝度値の代表値と、他の画像領域に含まれる複数の画素の輝度値の代表値との比は考慮せずに、前記対象空間の明るさ感を予測する、
    　ことを特徴とする請求項２に記載の明るさ感予測装置。     The brightness prediction unit is a representative value of the brightness values of a plurality of pixels included in the image region whose surface type is the floor surface among the plurality of image regions, and the brightness of the plurality of pixels included in the other image regions. Predicting the feeling of brightness in the target space without considering the ratio of the value to the representative value.
    The brightness feeling prediction device according to claim 2.
  4. 　前記明るさ感予測部は、
    　間欠的に前記対象空間の明るさ感を予測し、
    　直前に予測された前記対象空間の明るさ感と、今回予測した前記対象空間の明るさ感との差分に基づいて、今回予測した前記対象空間の明るさ感を補正する、
    　ことを特徴とする請求項１から３のいずれか１項に記載の明るさ感予測装置。     The brightness prediction unit is
    Intermittently predict the brightness of the target space,
    The brightness feeling of the target space predicted this time is corrected based on the difference between the brightness feeling of the target space predicted immediately before and the brightness feeling of the target space predicted this time.
    The brightness feeling prediction device according to any one of claims 1 to 3, wherein the brightness feeling predicting device is characterized.
  5. 　コンピュータを、
    　対象空間を表す輝度画像に含まれる各面に対応する各画像領域の面種別を設定する面種別設定部と、
    　各面種別に対して明るさ感への寄与度を示す重みが関連付けられた重み情報を参照し、複数の前記画像領域それぞれについての、当該画像領域に含まれる複数の画素の輝度値及び当該画像領域の面種別の重みに基づいて、前記対象空間の明るさ感を予測する明るさ感予測部と、
    　として機能させることを特徴とする明るさ感予測プログラム。     Computer,
    A surface type setting unit that sets the surface type of each image area corresponding to each surface included in the luminance image representing the target space, and a surface type setting unit.
    With reference to the weight information associated with the weight indicating the degree of contribution to the feeling of brightness for each surface type, the brightness values of the plurality of pixels included in the image area and the image for each of the plurality of image areas. A brightness prediction unit that predicts the brightness of the target space based on the weight of the surface type of the region,
    Brightness prediction program characterized by functioning as.
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JP2010169583A (en) * 2009-01-23 2010-08-05 Toyota Central R&D Labs Inc Illumination environment determination apparatus and program
JP2013206812A (en) * 2012-03-29 2013-10-07 Iwasaki Electric Co Ltd Lighting control system

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CN117011189A (en) * 2023-09-01 2023-11-07 中认尚动（上海）检测技术有限公司 Space brightness evaluation method
CN117011189B (en) * 2023-09-01 2024-03-19 中认尚动（上海）检测技术有限公司 Space brightness evaluation method

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