Information processing device

Abstract

To enable evaluation of an area that can be monitored by a surveillance camera.SOLUTION: An information processing device disclosed herein is configured to evaluate the size of a monitorable area, within an area included in a given space, that can be monitored by a given surveillance camera on the basis of structure information regarding a structure existing in the given space, material information on a surface material of the structure, and illumination light information on illumination light illuminating the given space.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a surveillance camera. [Background technology]

[0002] Systems for optimizing surveillance by surveillance cameras are known. For example, Patent Document 1 discloses an invention related to a system that changes or corrects the surveillance area of ​​a surveillance camera based on structure information. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2017-225108 [Patent Document 2] Patent Publication No. 2021-010069 Summary of the Invention [Problem to be solved by the invention]

[0004] The present disclosure aims to evaluate areas that can be monitored by surveillance cameras. [Means for solving the problem]

[0005] One aspect of an embodiment of the present disclosure is This information processing device has a control unit that evaluates the size of a monitorable area, which is an area that can be monitored by a specified surveillance camera, within an area included in a specified space based on structure information regarding structures present in the space, material information regarding the surface material of the structures, and illumination light information regarding the illumination light that illuminates the specified space.

[0006] Other aspects include a method executed by the information processing device, a program for causing a computer to execute the method, or a computer-readable storage medium non-temporarily storing the program. [Effects of the Invention]

[0007] According to the present invention, it is possible to evaluate an area that can be monitored by a surveillance camera. [Brief explanation of the drawings]

[0008] [Figure 1] An overview diagram to explain the space to be monitored. [Figure 2] FIG. 2 is a diagram illustrating the module configuration of the evaluation device 1. [Figure 3] FIG. 2 is a diagram for explaining data stored in a storage unit 12. [Figure 4] 4 is a flowchart of a process executed in the first embodiment. [Figure 5] 4 is a flowchart of a process executed in the first embodiment. [Figure 6] 10 shows an example of object data used in the second embodiment. [Figure 7] 10 is a flowchart of a process executed in a second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] It is common to use multiple surveillance cameras to monitor a given space, such as the interior of a commercial facility. When using multiple surveillance cameras to monitor a facility, it is preferable to determine their placement positions so as to minimize blind spots.

[0010] As a related technology, for example, information about the positions of structures placed in a space is used to calculate the areas that can be captured by each of multiple surveillance cameras, thereby reducing blind spots. There is a system that determines the placement of surveillance cameras so that areas that cannot be monitored are not covered by the camera, for example, areas that are hidden by pillars.

[0011] However, since such systems do not utilize information other than that of the structure, there may be cases where the range that can be monitored cannot be properly estimated. For example, consider a case where ambient light (such as sunlight) enters a monitored space from outside the building. If the sunlight reflects off the internal structures, glare may appear in the image captured by the camera, resulting in areas that cannot be monitored adequately. To solve this problem, it is preferable to simulate the area that can be monitored by a surveillance camera, taking into account the reflection of light. The information processing device according to the present disclosure solves such problems.

[0012] An information processing device according to one embodiment has a control unit that evaluates the size of a monitorable area, which is an area that can be monitored by a specified surveillance camera, within an area included in the specified space, based on structure information regarding structures present in the specified space, material information regarding the surface material of the structures, and illumination light information regarding the illumination light that illuminates the specified space.

[0013] The predetermined space is a space to be monitored, and is typically an indoor space. The structure information is information about fixed structures within the space. The structure information may be, for example, information about the shape, size, location, etc. of one or more structures. The structure information may also include information about openings (e.g., windows) provided in the structure. The structure information may be data representing the location of multiple structures within a three-dimensional space.

[0014] The material information is information about the surface material of the structure represented by the structure information. The material information may include, for example, information for identifying the surface material and information about the light reflectance of each material.

[0015] The illumination light information is information about the illumination light that illuminates a specified space. The illumination light may be sunlight or artificial light. The illumination light information may include information about the intensity and incident angle of the illumination light. Furthermore, if the illumination light is sunlight, the illumination light information may include information about the altitude and direction of the sun.

[0016] The control unit evaluates the size of the area that can be monitored by multiple surveillance cameras placed in a space based on the three pieces of information mentioned above. The monitorable area refers to an area that can be adequately monitored by a surveillance camera. The monitorable area may be a three-dimensional area. The monitorable area does not necessarily coincide with the area that can be imaged by the surveillance camera. As mentioned above, if there is an area within the area that can be physically imaged by the surveillance camera (referred to as the image capture area) that is difficult to see due to light reflection, the monitorable area will be narrowed accordingly.

[0017] By using the structure information, the control unit can determine the physical blind spot from a specific position and determine the imaging area corresponding to a certain surveillance camera. Furthermore, by using the illumination light information and material information, the control unit can, for example, simulate light reflection. This makes it possible to determine when a part of the imaging area cannot be monitored due to reflected illumination light (i.e., the monitorable area is narrower than expected).

[0018] Furthermore, the control unit may determine positions where the multiple surveillance cameras should be installed based on the evaluation results. For example, the control unit may determine the installation positions of the surveillance cameras so that the size of the monitorable area is maximized.

[0019] The control unit may also simulate the reflection of light illuminating a specified space based on structure information and material information, and determine as a monitorable area an area where the intensity of reflected light as seen from the surveillance camera is below a specified value.

[0020] Furthermore, the control unit may perform a simulation for each time period, and determine the placement positions of the multiple surveillance cameras for each time period based on the results of the simulation.

[0021] The control unit may also acquire object information regarding a dynamic object moving within a predetermined space, and evaluate the monitorable area further based on the results of simulating the movement of the dynamic object.

[0022] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. The configurations of the following embodiments are examples, and the present disclosure is not limited to the configurations of the embodiments.

[0023] (First embodiment) An overview of an evaluation device according to a first embodiment will be described below. The evaluation device according to this embodiment is a device that determines the optimal placement position of a surveillance camera within a predetermined space.

[0024] First, we will explain the optimal placement of surveillance cameras. Figure 1 is a plan view showing an example of a space to be monitored by multiple surveillance cameras. The space to be monitored can be, for example, the interior of a commercial facility such as a store.

[0025] 1, hatched areas represent structures that obstruct visibility, such as walls and pillars. Pillars indicated by reference numerals 103A and 103B exist within the facility. Reference numeral 105 denotes a glass window, and reference numeral 106 denotes a glass entrance. External ambient light enters through the glass. In addition, the store also contains shelves for displaying products and a cash register. The shelves and counters can also be considered part of the structure.

[0026] Here, we consider an example in which the interior of such a store is monitored by multiple surveillance cameras. Reference numeral 101 denotes a surveillance camera installed in one corner of the store. The surveillance camera has a predetermined viewing angle. Here, surveillance camera 101 is capable of capturing an image of the range indicated by reference numeral 102. In the following explanation, the three-dimensional area that each camera can capture without any physical barriers will be referred to as the "capture area." In order to thoroughly monitor the inside of such a store, it is preferable to arrange the surveillance cameras so that the imaging areas of the multiple surveillance cameras can cover the entire area inside the store.

[0027] However, there are cases where this alone does not result in areas that cannot be monitored by any of the surveillance cameras. For example, in the example of FIG. 1, assume that sunlight is incident from outside in the direction of the dotted arrow. Also, assume that the surface of pillar 103B is made of a material with high light reflectivity. In such a case, sunlight incident from outside the building may be reflected by pillar 103B and enter the lens of surveillance camera 101. In such a case, glare or the like may occur in a part of the imaging area (for example, area 104 in FIG. 1), causing part of the image to be missing (i.e., an area that cannot be monitored). In such a case, a separate surveillance camera must be placed to monitor area 104. The occurrence of such a phenomenon cannot be predicted based on the position information of the structure alone.

[0028] The evaluation device 1 in this embodiment performs light simulation in addition to the position information of the structure. By performing this process, the area monitored by the multiple surveillance cameras is evaluated, and the optimal placement positions of the surveillance cameras are determined based on the evaluation results.

[0029] [Device configuration] FIG. 2 is a diagram showing an example of the configuration of the evaluation device 1. The evaluation device 1 is a computer such as a server device, a personal computer, a smartphone, a mobile phone, a tablet computer, a personal digital assistant, etc. The evaluation device 1 includes a control unit 11, a storage unit 12, and an input / output unit 13.

[0030] The evaluation device 1 can be configured as a computer having a processor (CPU, GPU, etc.), a main memory device (RAM, ROM, etc.), and an auxiliary memory device (EPROM, hard disk drive, removable media, etc.). The auxiliary memory device stores an operating system (OS), various programs, various tables, etc., and by executing the programs stored therein, various functions (software modules) that match predetermined purposes, as described below, can be realized. However, some or all of the functions may be realized as hardware modules using hardware circuits such as ASICs and FPGAs.

[0031] The control unit 11 is a computing unit that executes a predetermined program to realize various functions of the evaluation device 1. The control unit 11 can be realized by, for example, a hardware processor such as a CPU. The control unit 11 may also be configured to include RAM, ROM (Read Only Memory), cache memory, etc.

[0032] The control unit 11 is configured to have three software modules: a data acquisition unit 111, a simulation unit 112, and a result output unit 113. Each software module may be realized by the control unit 11 (CPU) executing a program stored in the storage unit 12, which will be described later.

[0033] The data acquisition unit 111 acquires data for evaluating the installation positions of surveillance cameras in a predetermined space. In this embodiment, the data acquisition unit 111 acquires data on structures existing in the target space (hereinafter referred to as structure data), data on the surface materials of the structures (hereinafter referred to as material data), and data on ambient light (hereinafter referred to as ambient light data).

[0034] The simulation unit 112 simulates the area that can be monitored by each of the multiple surveillance cameras based on the data acquired by the data acquisition unit 111. The simulation includes a simulation of ambient light.

[0035] The result output unit 113 generates and outputs information relating to an optimal placement of multiple surveillance cameras based on the results of the simulation performed by the simulation unit 112.

[0036] The storage unit 12 is a means for storing information, and is configured with storage media such as RAM, a magnetic disk, a flash memory, etc. The storage unit 12 stores programs executed by the control unit 11, data used by the programs, etc.

[0037] The storage unit 12 stores the structure data, material data, and ambient light data acquired by the data acquisition unit 111.

[0038] An example of the structure data will now be described. Fig. 3(A) shows an example of the structure data. The structure data is data relating to the shape and size of a structure existing in a space. The structure data is composed of, for example, fields for a structure ID, a type, and location information. The structure ID field stores an identifier assigned to each structure. The type field stores the type of the structure (e.g., pillar, wall, window, etc.). The location information field stores data relating to the position of the structure in space. Examples of such data include a three-dimensional model of the structure, information about the size of the structure, and information about the placement position of the structure. By referring to the location information, the control unit 11 can identify the position of the structure in the space to be monitored. The structure data is available in the form of BIM (Building Information Modeling) models and 3D- The structure data may be a CAD model. The structure data may also include data relating to the structure of the building itself.

[0039] Next, an example of material data will be described below: Fig. 3(B) shows an example of material data. Material data is data related to the surface material of the structure indicated by the structure data. Material data is composed of fields such as a structure ID, a material ID, and characteristic information. The structure ID field stores an identifier assigned to each structure. The material ID field stores an identifier assigned to each surface material. The characteristic information field stores data related to the light reflection characteristics of the surface material. Examples of such data include the light reflection direction and reflectance. The reflection direction indicates the direction in which light is reflected when it hits the surface material. The reflectance indicates the proportion of incident light that is reflected (the proportion of light that is not absorbed by the material). In this example, the structure data and material data are separate, but they may be one type of data. By using a BIM model, etc., the two can be integrated.

[0040] Next, an example of the ambient light data will be described below: Fig. 3(C) shows an example of the ambient light data. The ambient light data is data related to the ambient light that illuminates the monitored space. Specifically, the ambient light data defines the direction and intensity of the incident ambient light. The ambient light data includes, for example, fields for type, lighting conditions, azimuth, and angle. The type field stores the type of ambient light (e.g., sunlight, artificial lighting, etc.). If the ambient light changes depending on the season or time of day, the lighting conditions field stores related data. For example, the position of the sun constantly changes throughout the day. Furthermore, the altitude of the sun changes throughout the year. In such cases, the lighting conditions field stores the conditions (e.g., data indicating the date and time of day). The azimuth field stores data indicating the azimuth angle at which the ambient light is incident. The angle field stores data indicating the angle at which the ambient light is incident (e.g., the solar elevation angle). In addition to the above, the ambient light data may also include data related to the characteristics of the ambient light (e.g., wavelength, etc.). In the example of FIG. 3(C), the azimuth angle and angle are defined for each lighting condition, but when defining a light source that moves continuously, such as the sun, these may be expressed by mathematical formulas.

[0041] Returning to Figure 2, we continue the explanation. The input / output unit 13 is a means for receiving input operations performed by an operator and presenting information to the operator. Specifically, the input / output unit 13 includes devices for input such as a mouse and a keyboard, and devices for output such as a display and a speaker. The input / output devices may be integrally configured with, for example, a touch panel display.

[0042] The specific hardware configuration of the evaluation device 1 may be appropriately determined depending on the embodiment. It is possible to omit, replace, or add components. For example, the control unit 11 may include multiple hardware processors. The hardware processor may be configured with a microprocessor, FPGA, GPU, etc. Furthermore, an input / output device other than those illustrated (for example, an optical drive, etc.) may be added. Furthermore, the evaluation device 1 may be configured with multiple computers. In this case, the hardware configurations of the computers may or may not be the same.

[0043] [flowchart] Next, a description will be given of the processing executed by the evaluation device 1 according to this embodiment. Fig. 4 is a flowchart of the processing executed by the evaluation device 1. The processing shown in the figure is started by an operation by the operator of the evaluation device 1.

[0044] First, in step S11, the data acquisition unit 111 acquires data (structure data) related to structures included in the space to be monitored. The structure data may be a file written in a predetermined format, or may be imported via the input / output unit 13. The operator of the device can generate structure data for the target space and import it into the evaluation device 1.

[0045] Next, in step S12, the data acquisition unit 111 acquires data (material data) related to the surface material of the structure. The material data may be a file written in a predetermined format, or may be imported via the input / output unit 13. The operator of the device can generate material data corresponding to the structure included in the target space and import it into the evaluation device 1.

[0046] Next, in step S13, the data acquisition unit 111 acquires data (ambient light data) related to the ambient light illuminating the space to be monitored. The ambient light data may be a file written in a predetermined format, or may be imported via the input / output unit 13. The operator of the device can generate ambient light data for the target space and import it into the evaluation device 1. If the ambient light is sunlight, the ambient light data may be data for tracking the position of the sun by date and by hour. If the ambient light is artificial light (e.g., lighting devices, luminous signs, displays, neon signs, etc.), the ambient light data may include data regarding the time of day when such light is generated.

[0047] Steps S14 to S18 are steps for arranging a virtual surveillance camera in the virtual space and simulating how it would look. These steps are executed by the simulation unit 112.

[0048] In step S14, multiple virtual surveillance cameras are temporarily placed in the virtual space. The number of surveillance cameras may be any number up to a predetermined value. The placement positions of the surveillance cameras may be determined by a general method.

[0049] Next, in step S15, the imaging area of ​​the temporarily placed multiple surveillance cameras is calculated. In this step, for example, based on the parameters of the surveillance cameras (e.g., angle of view, focal length, etc.), the area that is physically visible in the target space is identified. Furthermore, in this step, the imaging area is calculated based on the structure data acquired in step S11, taking into account the structures placed in the target space. The imaging area may be identified by coordinates in three-dimensional space.

[0050] Next, in step S16, calculations related to ambient light are performed, and the imaging area of ​​each monitoring camera is calculated. Areas that cannot be adequately monitored are excluded from the result, and the resulting area is designated as a monitorable area. In this step, a simulation of ambient light is performed to determine whether phenomena such as halation or glare due to ambient light occur in each surveillance camera. If an area that cannot be adequately monitored occurs due to such a phenomenon, that area (hereinafter referred to as an unmonitored area) is excluded from the imaging area. The remaining area is the monitorable area. A monitorable area is an area that can be monitored without being affected by external factors such as ambient light.

[0051] FIG. 5 is a flowchart showing in more detail the processing executed in step S16.

[0052] First, in step S161, a simulation of ambient light is performed. The simulation of ambient light may be performed, for example, by ray tracing. For example, the refraction and reflection of light that occur on the surface of an object are simulated based on the amount and direction of light emitted from a light source. In this case, if light is reflected on the surface of a structure, the angle and amount of reflection of light can be calculated using material data.

[0053] Next, in step S162, it is determined whether there is a surveillance camera that has an unmonitored area due to ambient light. In this step, it is determined for each of the multiple surveillance cameras whether light is incident with an intensity equal to or greater than a predetermined threshold. In this step, it is determined, for example, whether the luminous flux (or luminous flux per unit area) incident on the surface of the lens of the surveillance camera is equal to or greater than a predetermined threshold. Here, if there is a surveillance camera that is incident with light with an intensity equal to or greater than the predetermined threshold, it can be estimated that halation or glare occurs in the image captured by that surveillance camera. It can also be estimated that the occurrence of halation or glare will result in areas in the image where the object is not fully visible.

[0054] If there is a surveillance camera with an unmonitored area, the process proceeds to step S163. In step S163, the unmonitored area is excluded from the imaging area of ​​the surveillance camera, and the remaining area is set as the monitorable area. If there is no unmonitored area, the imaging area and the monitorable area will be equal. In this step, for example, a range on the lens surface where the light beam is incident with an intensity equal to or greater than a predetermined value may be identified, and the unmonitored area may be identified based on this range.

[0055] Returning to FIG. 4, the explanation will continue. In step S17, the result output unit 113 calculates an evaluation value for the provisionally placed surveillance camera arrangement. In this embodiment, the evaluation value increases as the monitorable area within the area included in the monitored space increases. The evaluation value may be, for example, a value that represents the volume of the monitorable area relative to the volume of the monitored space as a percentage. The evaluation value may indicate a higher evaluation as the ratio of the monitorable area to the area included in the monitored space increases. When the same area can be monitored by multiple monitoring cameras, the volume of the monitorable area may not be counted twice.

[0056] The monitored space may also be weighted. For example, if there is an area within the monitored space that should be monitored intensively, a larger weight may be assigned to that area before calculating the evaluation value. In this case, if the area can be monitored by multiple monitoring cameras, a larger evaluation value may be assigned to that area.

[0057] In step S18, the result output unit 113 determines whether the calculated evaluation value is equal to or greater than a predetermined threshold. If the calculated evaluation value is below the predetermined threshold, the process returns to step S14, and the temporary placement of the surveillance cameras is performed again.

[0058] When performing the provisional placement of the surveillance cameras multiple times, the placement positions of the surveillance cameras may be shifted by a predetermined value to cover all possible placement patterns. Alternatively, multiple placement patterns of the surveillance cameras may be set in advance, and the surveillance cameras may be provisionally placed according to the multiple placement patterns. Various methods used in optimization calculations may be used to determine the placement positions.

[0059] In step S18, if the calculated evaluation value is equal to or greater than a predetermined threshold, the process proceeds to step S19, where the result output unit 113 outputs the processing result. The processing result may include the locations of the multiple surveillance cameras, information about the imaging area, information about the unmonitored area, information about the monitorable area, the calculated evaluation value, and the like. Furthermore, the processing result may include the results of simulating ambient light. For example, if glare or the like caused by sunlight occurs during a specific time period, information about that time period and the unmonitored area may be output as part of the processing result. For example, information such as "In the evening, there is a risk that areas will be difficult to see due to the setting sun shining in" may be output.

[0060] As described above, the evaluation device according to this embodiment evaluates the area that can be monitored by a surveillance camera based on information about structures located within a given space and information about the surface materials of the structures. In particular, by simulating ambient light using information about the surface materials of the structures, it becomes possible to accurately detect phenomena that impede monitoring due to light reflection.

[0061] (Second embodiment) In the first embodiment, the placement position of the surveillance camera is evaluated taking into consideration the reflection of ambient light. However, factors other than ambient light can also be considered as factors that hinder surveillance. For example, when the object to be monitored is a commercial facility or a parking lot, the view of the surveillance camera may be temporarily obstructed by the movement of people or vehicles.

[0062] Here, we consider the deployment of multiple surveillance cameras in a store for the purpose of automatic payment for products. In order to determine when a customer has taken an item from a shelf, it is necessary to capture the customer's hand on video. However, as the number of customers increases, the target's hand may become obscured by shadows.

[0063] To address this issue, the second embodiment simulates the movement of an object moving within a monitored area, calculates unmonitored areas due to the object (for example, areas that become invisible due to being in the shadow of the object), and then corrects the evaluation value. An object is typically a moving object such as a person, a car, a bicycle, or personal mobility device. The object may be a living thing or an inorganic object.

[0064] In the second embodiment, the storage unit 12 is configured to further store data relating to objects that move within a space (hereinafter referred to as object data). FIG. 6 shows an example of object data.

[0065] The object data includes multiple virtual objects. In the example of Fig. 6, three virtual people are defined. The object data includes fields for object ID, type, shape data, time information, and movement data.

[0066] The object ID field stores the identifier of a virtual object. The type field stores the type of object, such as a person or a car. The shape data field stores data (shape data) related to the shape and size of the object. When the object is a person, the shape data may be data relating to height, sex, etc. When the object is a car, the shape data may be data relating to the class, shape, size, etc. of the car. The shape data may also be three-dimensional modeling data.

[0067] The time information field stores information about the time period and time when the corresponding object appears in the area to be monitored. For example, a certain virtual person may have information such as "visits during lunchtime on weekdays."

[0068] The movement data field stores data related to the movement of the corresponding object. For example, if the monitored object is a store, the movement data may be data defining the movement of customers from the time they enter the store until they leave (time-series changes in their positions). The movement data may be automatically generated based on typical behavioral patterns of customers.

[0069] The object data may be prepared by a user of the evaluation device, or may be generated based on previously observed object movements, or may be generated using a machine learning model or the like.

[0070] In the second embodiment, the simulation unit 112 is configured to be able to simulate the movement of an object in addition to simulating the ambient light. Furthermore, the simulation unit 112 updates the evaluation value (the evaluation value obtained by the simulation result of the ambient light) based on the result of simulating the movement of the object. This makes it possible to evaluate the placement position of a surveillance camera taking into account both the ambient light and the movement of the object.

[0071] 7 is a flowchart of the processing executed by the control unit 11 in the second embodiment. Processing that is the same as in the first embodiment is indicated by dashed lines, and a description thereof will be omitted.

[0072] After acquiring the ambient light data in step S13, the data acquisition unit 111 acquires object data in step S13A. The object data may be a file written in a predetermined format, or may be imported via the input / output unit 13. The operator of the device can generate ambient light data for the target space and import it into the evaluation device 1. The acquired object data is stored in the storage unit 12.

[0073] When the evaluation value is generated in step S17, the simulation unit 112 places a virtual object in the virtual space based on the object data, and simulates its movement (step S17A).

[0074] In this step, the simulation unit 112 simulates the movement of the object for a predetermined time width and calculates the area that is blocked by the object within the monitorable area of ​​each surveillance camera for each time step (e.g., every second). For example, the simulation unit 112 calculates that, in a certain time step, 3% of the monitorable area of ​​a certain surveillance camera is blocked by the object.

[0075] By performing this process for all time steps, it is possible to calculate the average percentage of the entire area that is occluded by an object over a specified time span. For example, if no object is present, 100% of the monitorable area is monitorable, whereas if an object is present, the size of the monitorable area drops to an average of 90% of the original value.

[0076] The result output unit 113 applies the calculation result to the evaluation value obtained in step S17, and updates the evaluation value. In this step, the evaluation value is corrected to be lower as the area occluded by the object becomes larger and the time period during which occlusion by the object occurs becomes longer. Any method can be used to correct the evaluation value. In step S18, the evaluation value thus obtained is used to make a judgment.

[0077] According to the second embodiment, it is possible to calculate an evaluation value for the placement of the surveillance cameras, taking into consideration occlusion caused by an object moving within the space to be monitored.

[0078] (Variation) The above-described embodiment is merely an example, and the present disclosure can be modified and implemented as appropriate within the scope that does not deviate from the gist of the disclosure. For example, the processes and means described in this disclosure can be freely combined and implemented as long as no technical contradiction occurs.

[0079] In addition, although the description of the embodiment does not particularly limit the time period for which the simulation is performed, the simulation may be performed after specifying a date or time period. Furthermore, multiple simulations may be performed for multiple dates or time periods. In this case, multiple simulations can be performed using ambient light data and object data corresponding to the specified dates and time periods. In this case, the optimum positions for installing the surveillance cameras may be output for each date and time period based on the evaluation values ​​obtained for each date and time period.

[0080] Furthermore, the evaluation device 1 may divide the target time period into predetermined time slots (for example, every 30 minutes) and determine the optimum placement position of the surveillance camera for each time slot.

[0081] In addition, in the description of the embodiment, the term "location of a surveillance camera" is used to mean the coordinates where the surveillance camera is located, but the location of a surveillance camera may also be a concept that includes the coordinates and angle (the direction in which the lens is facing) of the surveillance camera. In this case, in the loop of steps S14 to S18, the direction in which each surveillance camera is facing may be further changed while calculating the evaluation value. Furthermore, if the number and arrangement (coordinates) of the surveillance cameras are fixed, the evaluation value may be calculated while changing only the orientation in the loop of steps S14 to S18. In other words, the arrangement position may be a concept that includes only the orientation.

[0082] In addition, in the description of the embodiment, the surveillance cameras are fixed cameras, but the multiple surveillance cameras may be cameras whose placement positions can be dynamically changed (for example, mobility with cameras mounted on them). In this case, the evaluation device 1 may transmit instruction information instructing a control device that controls the placement positions of the surveillance cameras to a suitable position of the surveillance cameras. Furthermore, the multiple surveillance cameras may be cameras whose angles (orientations) can be dynamically changed. In this case, the evaluation device 1 may transmit instruction information instructing the angles (orientations) of the surveillance cameras to a control device that controls the angles of the surveillance cameras. Furthermore, if the preferred placement positions of the surveillance cameras differ for each time period (time slot), the evaluation device 1 may be configured to send the above-mentioned instruction information to the surveillance camera control device in order to change the placement positions of each surveillance camera for each time period.

[0083] In the description of the embodiment, the simulation unit 112 automatically generates the placement positions of the surveillance cameras, but the placement positions of the surveillance cameras may be specified by the operator of the evaluation device 1. In this case, the conditions related to the placement positions of the surveillance cameras, such as coordinates and directions, may be set by the operator of the evaluation device 1. The evaluation device 1 may acquire the size of the monitorable area under the specified conditions via the input unit 13 and output the evaluation value (or simulation result) under the specified conditions. That is, the evaluation device 1 may function as a device for evaluating the size of the monitorable area under the specified conditions.

[0084] Furthermore, a process described as being performed by one device may be shared and executed by multiple devices. Alternatively, a process described as being performed by different devices may be executed by a single device. In a computer system, the hardware configuration (server configuration) by which each function is realized can be flexibly changed.

[0085] The present disclosure can also be realized by providing a computer program implementing the functions described in the above embodiments to a computer, and having one or more processors in the computer read and execute the program. Such a computer program may be provided to the computer via a non-transitory computer-readable storage medium connectable to the computer's system bus or via a network. Non-transitory computer-readable storage media include, for example, any type of disk, such as a magnetic disk (e.g., a floppy disk, a hard disk drive (HDD), etc.), an optical disk (e.g., a CD-ROM, a DVD disk, a Blu-ray disk), a read-only memory (ROM), a random access memory (RAM), an EPROM, an EEPROM, a magnetic card, a flash memory, an optical card, or any type of medium suitable for storing electronic instructions. [Explanation of symbols]

[0086] 1. Evaluation device 11 Control section 12...Storage section 13...Input / output section

Claims

1. Structure information regarding structures present in a predetermined space; Material information regarding the surface material of the structure; illumination light information relating to illumination light illuminating the predetermined space; and simulating reflection of light illuminating the predetermined space based on the structure information, the material information, and the illumination light information; A control unit that evaluates the size of a monitorable area, which is an area included in the predetermined space and in which the intensity of reflected light as seen from a predetermined monitoring camera is equal to or less than a predetermined value, based on the results of the simulation. An information processing device having the above.

2. The control unit determines, based on the result of the evaluation, the positions of the plurality of monitoring cameras such that the size of the monitorable area is equal to or larger than a predetermined value. The information processing device according to claim 1 .

3. the illumination light information includes information regarding changes in the illumination light for each time period, the control unit determines the placement positions of the plurality of monitoring cameras for each time period based on the results of the simulation for each time period. The information processing device according to claim 2 .

4. The control unit further acquires object information regarding a dynamic object moving within the predetermined space; evaluating the monitorable area further based on a result of simulating the movement of the dynamic object; The information processing device according to claim 1 .

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