JP2020160892A - Image generator and image generation program - Google Patents

Abstract

To make it easy to recognize costs required when a camera is installed in a monitoring space.SOLUTION: An image generator 10 includes: a storage part 11 which stores structure information 21 representing respective positions and shapes of structures present in a monitoring space 30 and attribute information 22 representing respective attributes of the structures; an attachment candidate region calculation part 26 which calculates, based on monitoring target condition including a position of a monitoring target and the structure information 21, an attachment candidate region which is located in a region on the structure to which a camera for photographing the monitoring target is attached and which permits attachment of the monitoring target of the monitoring target condition in a photographable manner; a cost distribution calculation part 24 which calculates, based on rules for converting at least one of the structure information 21 and the attribute information 22 of each structure into costs required for attaching the camera to the structure, costs required when the camera is attached in the attachment candidate region; and an image generation part 27 which generates a cost distribution image 40 permitting cost identification for each attachment candidate region.SELECTED DRAWING: Figure 3

Description

The present invention relates to an image generator and an image generator.

When installing a surveillance camera, the placement conditions (installation position, posture, angle of view, etc.) of the surveillance camera to achieve the desired surveillance purpose are planned (planned) in advance. For example, if it is necessary to photograph the surveillance space without blind spots in order to achieve the surveillance purpose, the arrangement conditions of the surveillance cameras are determined so that the blind spots do not occur. Since the placement conditions are generally diverse, manual planning requires a great deal of labor and depends on the subjectivity and experience of the planner.

Therefore, the applicant finds the space range in which the camera can take a picture based on the placement condition, finds the evaluation value that becomes higher as the blind spot in the monitoring space decreases, and changes the placement condition to obtain the highest evaluation value. By searching for, we proposed a technique to easily obtain an arrangement condition with few blind spots without depending on the experience of the planner (Patent Document 1 below).

Japanese Unexamined Patent Publication No. 2018-128961

However, under the arrangement conditions obtained by the invention of Patent Document 1, it may actually be difficult to install in terms of cost. This is because the installation cost of the camera varies depending on, for example, the length of the wiring to be laid, the material and shape of the mounting location, and the like. Therefore, the planner could not easily determine whether or not it is cost-effective to install the camera according to the arrangement conditions obtained by the invention of Patent Document 1.
The present invention has been made in view of the above problems, and an object of the present invention is to make it easy to grasp the cost when the camera is installed in the surveillance space.

The image generation device according to one embodiment of the present invention includes a storage unit that stores at least spatial information including information on the position and shape of each structure existing in the monitoring space, and a monitoring target including the position of the monitoring target. A mounting candidate that calculates a mounting candidate area that is an area on a structure to mount a camera for shooting a monitoring target based on conditions and spatial information, and can mount the monitoring target under the monitoring target condition so that it can be shot. Cost distribution calculation that calculates the cost when a camera is mounted in the mounting candidate area based on the area calculation unit and the rule that converts the information for each structure included in the spatial information into the cost of mounting the camera on the structure. A unit and an image generation unit that generates a cost distribution image capable of identifying the cost for each mounting candidate region are provided.

The spatial information may include information related to wiring installed in the structure.
The spatial information may include at least one piece of information about the material, surface thickness and strength of the structure.

The cost distribution calculation unit may calculate the cost based on the height from the floor surface or the ground surface of the structure.
The cost distribution calculation unit may calculate the cost based on the positional relationship between the position in the mounting candidate area and the monitoring target.

An image generation program according to another embodiment of the present invention provides a computer with spatial information including at least information on the position and shape of each structure existing in the monitoring space and monitoring target conditions including the position of the monitoring target. Based on the above, a mounting candidate area calculation step for calculating a mounting candidate area that is an area on a structure for mounting a camera for shooting a monitoring target and to which a monitoring target under the monitoring target condition can be mounted so that the monitoring target can be photographed. A cost distribution calculation step for calculating the cost when a camera is mounted in the mounting candidate area and a mounting candidate based on a rule for converting the information for each structure included in the spatial information into the cost for mounting the camera on the structure. An image generation step of generating a cost distribution image in which the cost for each region can be identified is executed.

In the image generation method according to still another embodiment of the present invention, the computer is provided with spatial information including at least information on the position and shape of each structure existing in the monitoring space and monitoring target conditions including the position of the monitoring target. Based on the above, the mounting candidate area calculation step for calculating the mounting candidate area in which the monitoring target under the monitoring target condition can be mounted so as to be able to shoot, which is the area on the structure to which the camera for shooting the monitoring target is mounted. , A cost distribution calculation step to calculate the cost when a camera is mounted in the mounting candidate area based on the rule of converting the information for each structure included in the spatial information into the cost of mounting the camera on the structure, and mounting. An image generation step of generating a cost distribution image in which the cost for each candidate area can be identified is executed.

According to the present invention, it becomes easy to grasp the cost when the camera is installed in the surveillance space.

It is a schematic block diagram of an example of the image generation apparatus of embodiment of this invention. It is explanatory drawing of the example of a monitoring space and a structure. It is a figure which shows the 1st example of the cost distribution image which shows the cost distribution when the camera is installed in the structure. It is explanatory drawing of an example of structure information and attribute information. (A) and (b) are explanatory views of an example of the calculation method of the mounting candidate area for mounting a camera on a structure. It is a figure which shows the 2nd example of the cost distribution image which shows the cost distribution when the camera is installed in the structure. It is a flowchart of an example of the image generation method of embodiment of this invention.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. It should be noted that the embodiments of the present invention shown below exemplify devices and methods for embodying the technical idea of the present invention, and the technical idea of the present invention includes the structure, arrangement, etc. of components. Is not specified as the following. The technical idea of the present invention may be modified in various ways within the technical scope specified by the claims stated in the claims.

(Constitution)
See FIG. The image generation device 10 of the embodiment is composed of, for example, a computer, and includes a storage unit 11 and a control unit 12.
The storage unit 11 may include any of a semiconductor storage device, a magnetic storage device, and an optical storage device. The storage unit 11 may include a memory such as a register, a cache memory, a ROM (Read Only Memory) and a RAM (Random Access Memory) used as a main storage device.

The control unit 12 is composed of, for example, a processor such as a CPU (Central Processing Unit) or an MPU (Micro-Processing Unit), and peripheral circuits thereof.
The function of the control unit 12 described below is realized, for example, by executing the image generation program 20, which is a computer program stored in the storage unit 11, by a processor included in the control unit 12.

The input device 13 is a mouse operated by a camera planning operator, a monitoring worker, an administrator, or the like (hereinafter, referred to as “planning operator, etc.”) in order to control the operation of the image generation device 10. And keyboards. The input device 13 is connected to the image generation device 10, and various information is input to the image generation device 10 from the input device 13.

The image generation device 10 generates a cost distribution image representing a cost distribution when the camera is installed in a structure in a predetermined monitoring space.
The output device 14 is a display, a projector, a printer, or the like that outputs a cost distribution image generated by the image generation device 10.
See FIG. Now, suppose planning to install a surveillance camera in the indoor surveillance space 30. The present invention can also be applied to planning assuming an outdoor monitoring space.

The monitoring space 30 is surrounded by a relatively low low ceiling portion 31a, a relatively high high ceiling portion 31b, a floor 32, walls 33, 34 and 35, and a wall 36 (not shown). The low ceiling portion 31a, the high ceiling portion 31b, the floor 32, and the walls 33 to 36 are examples of structures existing in the monitoring space 30.
Further, in the monitoring space 30, there are line concentrators 39a, 39b and 39c capable of connecting the pillars 37 and 38 with the video transmission line and the power supply line of the camera. The line concentrators 39a, 39b and 39c may be, for example, a controller (control device), a recorder (recording device), a power supply device, or the like. These columns 37 and 38 and the concentrators 39a to 39c are examples of structures in the monitoring space 30.

The image generation device 10 generates, for example, the cost distribution image 40 shown in FIG. 3 based on the attribute information representing the attributes of these structures. The cost distribution image 40 illustrated in FIG. 3 shows the cost distribution when the camera is installed on the surfaces of the low ceiling portion 31a and the high ceiling portion 31b facing the monitoring space 30 side.
Hereinafter, the cost distribution image 40 when the cameras are installed on the low ceiling portion 31a and the high ceiling portion 31b will be described. However, the image generation device 10 includes a surface of the floor 32 and walls 33 to 36 facing the monitoring space 30 side. , When the camera is installed on the surfaces of the columns 37 and 38, a cost distribution image showing the cost distribution on these surfaces may be generated.

The area 41 with the grain hatching and the area 42 with the thin diagonal line hatching indicate the installation cost when the camera is installed on the low ceiling portion 31a. The dark diagonal line hatched area 43 and the grid-like hatched area 44 indicate the installation cost when the camera is installed on the high ceiling portion 31b.
The cost in region 41 is lower than the cost in region 42. The cost in region 42 is lower than the cost in region 43. Also, the cost in region 43 is lower than the cost in region 44.

The cost in the area 41 is lower than the cost in the area 42 because the area 41 is closer to the concentrators 39a and 39b than the area 42 and the wiring cost is lower.
Further, the cost in the area 43 is lower than the cost in the area 44 because the area 43 is closer to the concentrator device 39c than the area 44 and the wiring cost is lower.

Further, the cost in the areas 43 and 44 is higher than the cost in the areas 41 and 42 because the construction cost for installing the camera in the high ceiling portion 31b is higher than the construction cost for installing the camera in the low ceiling portion 31a. Is. As described above, the cost in the present embodiment is the installation cost obtained from the wiring cost and the construction cost when the camera is attached, and the cost distribution is the cost distribution calculated on the surface of the structure existing in the monitoring space 30. Is.
The image generation device 10 generates such a cost distribution image 40 and outputs it from the output device 14. As a result, the planner and the like can easily grasp the cost when the camera is installed in the monitoring space 30.

The details of the image generator 10 will be described below. See FIG. In addition to the image generation program 20 described above, the storage unit 11 stores structure information 21, attribute information 22, and monitoring target information 23. Information that combines the structure information 21 and the attribute information 22 is an example of spatial information in the present invention. Spatial information includes at least information on the position and shape of each structure, and preferably further includes attributes of each structure.
The structure information 21 is three-dimensional geometric shape data (that is, a three-dimensional model) representing the position and shape of a real-world structure that surrounds or exists in the monitoring space 30. Structures are, for example, structures, ground, obstacles (furniture, trees, etc.) and other objects. In the example of the monitoring space 30 of FIG. 2, the structure information 21 determines the positions and shapes of the low ceiling portion 31a and the high ceiling portion 31b, the floor 32, the walls 33 to 36, the pillars 37 and 38, and the concentrators 39a to 39c. Represent.

The attribute information 22 is attribute data representing the attributes of such a structure. In the example of the monitoring space 30 of FIG. 2, the attribute information 22 includes the low ceiling portion 31a and the high ceiling portion 31b, the floor 32, the walls 33 to 36 (however, the front wall 36 is not shown), the columns 37 and 38, Represents the attributes of the line concentrators 39a to 39c.
The attribute data of the structure may include, for example, the type, material, thickness, and strength of the structure.

The attribute data may include type data representing types such as "ceiling", "wall", "door", and "pillar". Further, the attribute data may include information on whether or not the structure functions as a "concentrator" and information on the position of the port to which the wiring is connected, that is, information on the wiring installed in the structure.
In addition, material data representing materials such as "gypsum board" and "steel frame" may be included. The attribute information 22 may include attribute data indicating whether or not the camera can be attached.

Such structure information 21 and attribute information 22 are set and registered in advance from the input device 13 by a planner or the like and stored in the storage unit 11.
FIG. 4 shows the structures in the monitoring space 30 of FIG. 2, that is, the low ceiling portion 31a and the high ceiling portion 31b, the walls 33 to 36, the columns 37 and 38, and the structure information 21 and attribute information 22 of the line concentrators 39a to 39c. It is a schematic diagram which shows.

See FIG. The monitoring target information 23 includes the monitoring target condition data regarding the monitoring target, which is an object to be monitored, arranged in the monitoring space 30, and attribute data such as the material of the monitoring target.
The monitoring target condition data includes, for example, the position where the monitoring target is arranged in the monitoring space 30, the three-dimensional shape of the monitoring target, the orientation of the monitoring target, the monitoring direction of the monitoring target, and the data of the required resolution of the image required for monitoring the monitoring target. May include.
The monitoring target information 23 is stored in the storage unit 11 when the monitoring target condition data and the attribute data of the monitoring target are set by the control unit 12 as needed. The monitoring target information 23 may be the coordinate information of the monitoring point at the position to be monitored.

The control unit 12 reads out the structure information 21 and the attribute information 22 stored in the storage unit 11. Further, the control unit 12 reads and executes the image generation program 20 stored in the storage unit 11 and functions as a cost distribution calculation unit 24, a monitoring target setting unit 25, a mounting candidate area calculation unit 26, and an image generation unit 27. To do.
Based on the structure information 21 and the attribute information 22, the cost distribution calculation unit 24 identifies the surface of the structure existing in the monitoring space 30 to which the camera can be attached.

For example, the cost distribution calculation unit 24 may specify the surface on which the camera can be attached based on the attribute data including the attribute information 22 indicating whether or not the camera can be attached.
Alternatively, the type of the structure to which the camera can be attached is set in advance for each type of camera, and the surface to which the camera can be attached is specified based on the type data of the structure included in the attribute information 22. Good.

Then, the cost distribution calculation unit 24 divides the surface on which the camera can be attached into a unit region having a predetermined size.
Next, the cost distribution calculation unit 24 calculates the camera installation cost for each unit area based on the attribute information 22. The cost distribution calculation unit 24 may calculate the installation cost by using the structure information 21 in addition to the attribute information 22. The size of the unit area may be appropriately determined according to the degree of fineness to be presented by the cost distribution image. Preferably, the size is set to be smaller than the installation surface of the camera mounting device (example: 10 × 10 cm). Further, the cost may be calculated as, for example, the cost when it is attached to the center of gravity of the unit area.

For example, the cost distribution calculation unit 24 may calculate the construction cost when mounting the camera in the unit area as the installation cost.
For example, the cost distribution calculation unit 24 may calculate the construction cost based on attribute data such as material, thickness, shape, and strength included in the attribute information 22. For example, a construction method, a tool, and a mounting bracket suitable for each attribute such as material, thickness, shape, and strength are stored in the storage unit 11 in advance in association with attribute data as parameters. Further, the cost of using each of the construction method, the tool, and the mounting bracket is stored in the storage unit 11 in advance.

The cost distribution calculation unit 24 may calculate the construction cost according to a conversion rule for accumulating the usage costs of the construction method, tools, and mounting brackets associated with the attribute data.
In addition, the construction cost may include the cost of using the necessary equipment required to mount the camera in each unit area. An example of the necessary equipment is an aerial work platform for mounting a camera in a high place. The cost distribution calculation unit 24 may determine the height from the floor surface to each unit area based on the structure information 21 and calculate the usage cost of the necessary equipment.
For example, the required height of the aerial work platform and the cost of using it may be stored in advance in the storage unit 11 as parameters. The cost distribution calculation unit 24 may calculate the construction cost according to a conversion rule for determining whether or not to add the usage cost of the aerial work platform according to the height of the unit area from the floor surface (ground).

Further, the cost distribution calculation unit 24 may calculate the wiring cost of the video transmission line and the power supply line of the camera attached to the unit area as the installation cost. The cost distribution calculation unit 24 may calculate the total of the construction cost and the wiring cost as the installation cost.
For example, the wiring cost per unit length may be stored in advance in the storage unit 11 as a parameter.
The cost distribution calculation unit 24 identifies the positions of the concentrators 39a to 39c based on the structure information 21 and the attribute information 22, and uses a given route determination method to move from each unit area to the concentrators 39a to 39c. Determine the wiring route. The cost distribution calculation unit 24 may calculate the wiring cost according to a conversion rule that multiplies the wiring path length (for example, the shortest path length) by the wiring cost per unit length.

Then, the image generation unit 27 generates a cost distribution image 40 showing the distribution of the installation cost on the surface of the structure, and outputs the cost distribution image 40 from the output device 14 (see FIG. 3).
The cost distribution image 40 may be, for example, a grid-like distribution map showing the cost for each unit area. Further, in order to make the distribution easy to understand, colors may be displayed separately for each cost as needed. As shown in FIG. 3, the types of hatching may be divided according to cost.

The monitoring target setting unit 25 sets the monitoring target as needed. Specifically, the monitoring target condition data for arranging the monitoring target in the monitoring space 30 and the attribute data such as the material of the monitoring target are set.
For example, the monitoring target setting unit 25 sets the monitoring target condition data and the attribute data of the monitoring target based on the data input by the planner or the like using the input device 13.
The monitoring target setting unit 25 may set a plurality of monitoring targets.

The mounting candidate area calculation unit 26 calculates a mounting candidate area for mounting the camera on the structure, at least based on the monitoring target condition data to be monitored and the structure information 21.
For example, the mounting candidate area calculation unit 26 determines whether or not the light beam reaches the monitoring target without being blocked by other structures, assuming that the light source is arranged in each unit area.

The mounting candidate region calculation unit 26 calculates a set of unit regions in which light sources that emit light rays that have reached the monitoring target are arranged as mounting candidate regions.
At that time, the mounting candidate area calculation unit 26 may determine the maximum allowable distance from the monitoring target to the camera according to the required resolution specified in the monitoring target condition data of the monitoring target. The mounting candidate area calculation unit 26 may exclude a region farther than the maximum allowable distance from the mounting candidate area.

Further, the mounting candidate area calculation unit 26 may calculate the mounting candidate area according to the monitoring direction of the monitoring target specified in the monitoring target condition data.
See (a) in FIG. The columns 37 and 38 and the line concentrators 39a to 39c are omitted for the sake of clarity in the drawings.
For example, the mounting candidate area calculation unit 26 has a locus of a half straight line forming an allowable angle θ (0 ° ≦ θ <90 °) with a reference straight line 51 extending in the monitoring direction with a monitoring point on the surface of the object 50 to be monitored as one end. The cone-shaped space 53 formed by is calculated. The recommended monitoring direction is a direction toward the outside of the object to be monitored, and the weight-shaped space 34 is a space including a reference straight line. The permissible angle θ indicates the permissible range in the direction in which the monitored object is photographed.

Then, the mounting candidate area calculation unit 26 calculates a subspace of the cone-shaped space 53 that does not overlap with the space occupied by the structure as a photographable space to be monitored. However, the cone-shaped space 53 is regarded as the space generated by the spotlight light source, and the space behind the structure is excluded from the photographable space. That is, the space that becomes the blind spot of the structure when viewed from the monitoring point is excluded from the photographable space.
The mounting candidate area calculation unit 26 calculates a region of the surface of the structure that is in contact with the photographable space as a mounting candidate region. In the example of FIG. 5A, the region 54 in contact with the photographable space in the low ceiling portion 31a is calculated as the mounting candidate region.

The mounting candidate area calculation unit 26 may determine the maximum allowable distance from the monitoring target to the camera according to the required resolution specified in the monitoring target condition data of the monitoring target.
See (b) in FIG. The mounting candidate region calculation unit 26 calculates the region 56 excluding the region 55 that is farther than the maximum allowable distance as the mounting candidate region.

See FIG. The image generation unit 27 displays the installation cost of the unit area that overlaps with the installation candidate area among the unit areas for which the installation cost is calculated so as to be identifiable, and displays the cost distribution image 40 that does not display the installation cost of the other unit areas. Generate. That is, the image generation unit 27 generates the cost distribution image 40 that does not display the installation cost of the unit area that does not overlap with the mounting candidate area in the cost distribution image 40 of FIG.

See FIG. Reference numerals 50a, 50b and 50c indicate monitoring targets, and reference numerals 56a, 56b and 56c indicate mounting candidate regions for attaching cameras for photographing the monitoring targets 50a, 50b and 50c to the structure. The region corresponding to the low ceiling portion 31a and the region corresponding to the high ceiling portion 31b may be color-coded so that they can be distinguished. In the example of the cost distribution image 40 of FIG. 6, shaded hatching is applied to the region corresponding to the high ceiling portion 31b.
As shown, only the costs of the unit areas that overlap with the mounting candidate areas 56a, 56b and 56c are displayed, and the unit areas that do not overlap with the mounting candidate areas 56a, 56b and 56c are excluded. The image generation unit 27 outputs the cost distribution image 40 from the output device 14.

The cost distribution calculation unit 24 may correct the installation cost in each unit area according to the monitoring target condition data of the monitoring target.
For example, the installation cost may be corrected according to the performance of the camera required to photograph the monitored object from the position of each unit area. For example, unless the camera has a long distance from the position of the unit area to the monitoring target and a large number of shooting pixels, the installation cost will be high if the required resolution specified in the monitoring target condition data cannot be satisfied. Therefore, the cost distribution calculation unit 24 may correct the installation cost by the increased camera cost. That is, the cost distribution calculation unit 24 may correct the installation cost according to the distance between each unit area and the monitoring target. In other words, the cost distribution calculation unit 24 may correct the installation cost based on the positional relationship with the monitored object.

Further, when the areas overlap as in the mounting candidate areas 56a and 56b in FIG. 6 and a plurality of monitoring targets can be simultaneously photographed by the cameras installed in the overlapping areas, the plurality of monitoring targets 50a and 50b should be photographed at the same time. A camera can be installed in. Therefore, for example, the installation cost per camera may be divided between a plurality of monitoring targets 50a and 50b to obtain the installation cost for each monitoring target.
That is, the cost distribution calculation unit 24 may obtain the installation cost in the range where the mounting candidate regions overlap from the installation cost calculated when the mounting candidate regions do not overlap. For example, when two monitoring targets can be photographed at the same time with one camera, the installation cost of the overlapping area may be half the cost of the area where the mounting candidate areas do not overlap.

Further, as shown in FIG. 6, the image generation unit 27 is not limited to generating the cost distribution image 40 in which the installation cost of the camera in each unit area in the mounting candidate areas 56a, 56b, and 56c is identifiable. , A cost distribution image 40 may be generated in which a representative value of the cost is identifiable for each mounting candidate region.
For example, the highest value or the lowest price (or the price difference between the highest price and the lowest price) in the cost of each unit area in the mounting candidate area is used as a representative value of the cost, and these representative values are identified for each mounting candidate area. You may generate a cost distribution image that is displayed as possible.
The cost distribution calculation unit 24 calculates the installation cost in each unit area in the installation candidate area calculated by the installation candidate area calculation unit 26, obtains the cost distribution in the installation candidate area, and the image generation unit 27 The cost distribution image 40 may be generated based on the cost distribution.

(motion)
An example of the image generation method of the embodiment will be described with reference to FIG. 7.
In step S1, prior to designing the camera installation position, the structure information 21 and the attribute information 22 of the structure existing in the monitoring space 30 are acquired or generated, and set and registered in the storage unit 11 of the image generation device 10. ..
The control unit 12 reads out the structure information 21 and the attribute information 22 stored in the storage unit 11.

In step S2, the cost distribution calculation unit 24 identifies the surface of the structure facing the monitoring space 30 side to which the camera can be attached, based on the structure information 21 and the attribute information 22. The cost distribution calculation unit 24 divides the surface on which the camera can be attached into unit regions of a predetermined size.
In step S3, the cost distribution calculation unit 24 calculates the installation cost when the camera is installed in each unit area based on the structure information 21 and the attribute information 22.

In step S4, the monitoring target setting unit 25 determines whether or not to set the monitoring target. When the monitoring target is not set (step S4: N), the process proceeds to step S7. In this case, as shown in FIG. 3, the image generation unit 27 generates a cost distribution image 40 showing the cost distribution over the entire surface of the structure facing the monitoring space 30 side. The image generation unit 27 ends the process after outputting the cost distribution image 40 to the output device 14.

When the monitoring target is set in step S4 (step S4: Y), the monitoring target setting unit 25 sets the monitoring target condition data of the monitoring target and the attribute data such as the material, and the process proceeds to step S5.
In step S5, the mounting candidate area calculation unit 26 calculates a mounting candidate area for mounting the camera on the structure based on at least the monitoring target condition data of the monitoring target and the structure information.

In step S6, the cost distribution calculation unit 24 corrects the installation cost in each unit area according to the monitoring target condition data of the monitoring target.
In step S7, as shown in FIG. 6, the image generation unit 27 retains the unit area that overlaps with the mounting candidate area among the unit areas for which the installation cost is calculated, and excludes the other unit areas from the cost distribution image 40. Generate. The image generation unit 27 ends the process after outputting the cost distribution image 40 to the output device 14.

(Effect of embodiment)

(1) The storage unit 11 stores spatial information including at least structure information 21 representing the position and shape of each structure existing in the monitoring space. The mounting candidate area calculation unit 26 calculates a mounting candidate area for mounting the camera for photographing the monitoring target on the structure based on the monitoring target condition including the position of the monitoring target and the structure information. The cost distribution calculation unit 24 calculates the cost distribution when the camera is mounted in the mounting candidate area based on the rule of converting the information of the structure included in the spatial information into the cost of mounting the camera on the structure. The image generation unit 27 generates a cost distribution image 40 representing the cost distribution.

This makes it easier for the planner and the like to grasp the cost when the camera is installed in the surveillance space. For example, a planner or the like can grasp the distribution of camera installation costs calculated according to the structure of the structure in which the camera is installed.
In addition, the planner and the like can grasp the mounting candidate area of the camera capable of photographing the monitoring target and the mounting cost in the mounting candidate area.

(2) The spatial information further includes the attribute information 22, and the attribute information 22 may include information related to the wiring installed in the structure. This makes it possible to calculate a cost distribution that reflects the wiring costs of the video transmission line and power supply line connected to the camera.
(3) The attribute information 22 may include at least one information among the material, surface thickness and strength of the structure. This makes it possible to calculate a cost distribution that reflects the construction cost according to the construction method, tools, and mounting brackets when mounting the camera.

(4) The cost distribution calculation unit 24 may calculate the cost distribution based on the height from the floor surface or the ground surface of the structure. This makes it possible to calculate a cost distribution that reflects the cost of using the equipment required by the height of the camera mounting position.
(5) The cost distribution calculation unit 24 may calculate the cost distribution based on the positional relationship between the position in the mounting candidate region and the monitoring target. As a result, the cost distribution that reflects the installation cost according to the positional relationship with the monitoring target can be calculated.

10 ... image generation device, 11 ... storage unit, 12 ... control unit, 13 ... input device, 14 ... output device, 20 ... image generation program, 21 ... structure information, 22 ... attribute information, 23 ... monitoring target information, 24 ... Cost distribution calculation unit, 25 ... Monitoring target setting unit, 26 ... Installation candidate area calculation unit, 27 ... Image generation unit, 30 ... Monitoring space, 31a ... Low ceiling part, 31b ... High ceiling part, 32 ... Floor, 33 ~ 36 ... wall, 37, 38 ... pillar, 39a-39c ... concentrator, 40 ... cost distribution image

Claims (7)

A storage unit that stores spatial information including at least position and shape information of each structure existing in the monitoring space, and a storage unit.
Based on the monitoring target condition including the position of the monitoring target and the spatial information, the area on the structure to which the camera for photographing the monitoring target is attached, and the monitoring target under the monitoring target condition can be photographed. A mounting candidate area calculation unit that calculates a mounting candidate area that can be mounted on the camera,
Cost distribution for calculating the cost when the camera is mounted in the mounting candidate area based on the rule of converting the information for each structure included in the spatial information into the cost of mounting the camera on the structure. Calculation part and
An image generation unit that generates a cost distribution image that can identify the cost for each mounting candidate region,
An image generator characterized by comprising. The image generation device according to claim 1, wherein the spatial information includes information related to wiring installed in the structure. The image generator according to claim 1 or 2, wherein the spatial information includes at least one information among the material, surface thickness, and strength of the structure. The image generation device according to any one of claims 1 to 3, wherein the cost distribution calculation unit calculates the cost based on the height of the structure from the floor surface or the ground surface. The image generation according to any one of claims 1 to 4, wherein the cost distribution calculation unit calculates the cost based on the positional relationship between the position in the mounting candidate region and the monitoring target. apparatus. On the computer
For each structure existing in the monitoring space, a camera for photographing the monitoring target is attached based on at least spatial information including information on the position and shape of the structure and monitoring target conditions including the position of the monitoring target. A mounting candidate area calculation step for calculating a mounting candidate region which is a region on the structure and in which the monitoring target under the monitoring target condition can be mounted so as to be photographable.
Cost distribution for calculating the cost when the camera is mounted in the mounting candidate area based on the rule of converting the information for each structure included in the spatial information into the cost of mounting the camera on the structure. Calculation steps and
An image generation step of generating a cost distribution image capable of identifying the cost for each mounting candidate region, and
An image generation program characterized by executing. On the computer
For each structure existing in the monitoring space, a camera for photographing the monitoring target is attached based on at least spatial information including information on the position and shape of the structure and monitoring target conditions including the position of the monitoring target. A mounting candidate area calculation step for calculating a mounting candidate region which is a region on the structure and in which the monitoring target under the monitoring target condition can be mounted so as to be photographable.
Cost distribution for calculating the cost when the camera is mounted in the mounting candidate area based on the rule of converting the information for each structure included in the spatial information into the cost of mounting the camera on the structure. Calculation steps and
An image generation step of generating a cost distribution image capable of identifying the cost for each mounting candidate region, and
An image generation method characterized by executing.

Images