System, control unit, control method, and program

By using control devices to generate and compare the feature information of the topics between multiple image capturing devices, the problem of tracking topics at different shooting positions and directions of the equipment is solved, and efficient topic tracking effects are achieved.

JP2025038870AActive Publication Date: 2025-03-19CANON KK
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Patent Information

Application Number
JP2024131210
Authority / Receiving Office
JP · JP
Patent Type
Applications
Current Assignee / Owner
Priority Date
2023-09-07
Filing Date
2024-08-07
Publication Date
2025-03-19
Estimated Expiration
2044-08-07

AI Technical Summary

Technical Problem

The prior art is difficult to effectively track specific subjects between multiple image capturing devices, especially when the shooting positions and orientations of these devices are not at the same time.

Method used

Using a system consisting of the first and second control devices, images are captured and processed by the first and second image capturing devices, respectively, and feature information of the subject is generated and compared to determine whether to switch control to ensure a tracking effect.

Benefits of technology

The ability to efficiently track a specific subject in the case of different shooting positions and directions between multiple image capturing devices is realized.

✦ Generated by Eureka AI based on patent content.

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  • Figure 2025038870000001_ABST
    Figure 2025038870000001_ABST
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Abstract

To provide a system that can track a specific subject with a plurality of imaging apparatuses different in photographing position and photographing direction.SOLUTION: A system includes: first and second imaging apparatuses that are different in photographing direction; and a first control unit and a second control unit that control the second imaging apparatus to track a predetermined subject on the basis of a first image picked up by the first imaging apparatus or a second image picked up by the second imaging apparatus. The second control unit has second generation means that generates second feature information of the subject included in the second image, and comparison means that compares first feature information generated by the first control unit with the second feature information generated by the second generation means. The first and second feature information are information that can specify that the same subject is photographed when the same subject is photographed by the plurality of imaging apparatuses different in photographing direction. The system switches between a first state in which the first control unit controls the second imaging apparatus and a second state in which the second control unit controls the second imaging apparatus, on the basis of a result from the comparison means.SELECTED DRAWING: Figure 3
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Description

[Technical field]

[0001] The present invention relates to a system for tracking a specific subject using a plurality of image capturing devices with different shooting positions and shooting directions. [Background technology]

[0002] There is a technology that tracks a specific subject using an imaging device that can automatically control the pan / tilt / zoom (PTZ) from a remote location. In this type of automatic tracking control, the PTZ is automatically controlled so that the subject to be tracked is positioned at a desired position within the shooting angle of view.

[0003] Patent Document 1 describes a technology for tracking a specific subject by linking an imaging device with a fixed wide-angle imaging angle (fixed-angle camera) with a PTZ function (PTZ camera). In Patent Document 1, even if the subject to be tracked moves outside the angle of view of the fixed-angle camera and cannot be captured, the movement of the subject to be tracked is predicted so that the subject can be captured by the PTZ camera.

[0004] Furthermore, Patent Document 2 describes a technology in which, when a subject to be tracked moves near the boundary of the imaging range of a first imaging device, template data of the subject to be tracked generated by the first imaging device is transmitted to a second imaging device, and the second imaging device takes over the tracking target. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2017-204795 A [Patent Document 2] Patent No. 3814779 Summary of the Invention [Problem to be solved by the invention]

[0006] However, in Patent Documents 1 and 2, the object to be tracked is identified by template matching, so when tracking a specific object using multiple imaging devices, the multiple imaging devices need to be arranged so that their shooting positions and shooting directions are close to each other. Therefore, when the shooting positions and shooting directions of the multiple imaging devices are arranged far apart, it becomes difficult to track a specific object using the multiple imaging devices.

[0007] The present invention has been made in view of the above-mentioned problems, and has as its object to realize a system that makes it possible to track a specific subject using a plurality of imaging devices with different shooting positions and shooting directions. [Means for solving the problem]

[0008] In order to solve the above problems and achieve the object, the present invention provides a system including a first imaging device and a second imaging device having different shooting directions, and a first control device and a second control device that control the second imaging device to track a predetermined subject based on a first image captured by the first imaging device or a second image captured by the second imaging device, wherein the first control device has a first generation means that generates first feature information of the predetermined subject included in the first image, and a first control means that controls the second imaging device to track the predetermined subject based on the first feature information, and the second control device has a second generation means that generates second feature information of the subject included in the second image, and a second generation means that generates second feature information of the subject included in the second image, and a second control means that generates the feature information generated by the first control device. a comparison means for comparing the first feature information generated by the second generation means with the second feature information generated by the second generation means, and a second control means for controlling the second imaging device to track the specified subject based on the second feature information, wherein the first feature information and the second feature information are information that can identify the same subject when the same subject is photographed by a plurality of imaging devices with different shooting directions, and based on a result of the comparison by the comparison means, switching is performed between a first state in which the first control device controls the second imaging device to track the specified subject based on the first feature information and a second state in which the second control device controls the second imaging device to track the specified subject based on the second feature information. Effect of the Invention

[0009] According to the present invention, it is possible to track a specific subject using a plurality of imaging devices with different shooting positions and shooting directions. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram illustrating an example of a system configuration according to a first embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of the hardware configuration of devices constituting the system of the first embodiment. [Diagram 3]FIG. 2 is a diagram illustrating an example of the functional configuration of an apparatus constituting the system of the first embodiment. [Figure 4] 4 is a flowchart illustrating a basic operation of the apparatus constituting the system of the first embodiment. [Diagram 5] 4A to 4C are diagrams for explaining a coordinate conversion method for a captured image according to the first embodiment. [Figure 6] 5A to 5C are views for explaining a subject detection method and a coordinate conversion method according to the first embodiment. [Figure 7] 5A to 5C are diagrams for explaining pan control according to the first embodiment. [Figure 8] 5A to 5C are diagrams for explaining tilt control according to the first embodiment. [Figure 9] 4 is a flowchart illustrating a control process according to the first embodiment. [Figure 10] 4A to 4C are diagrams for explaining a method for determining a subject to be tracked in the first embodiment. [Figure 11] FIG. 11 is a diagram illustrating an example of the functional configuration of an apparatus constituting a system according to a second embodiment. [Figure 12] 10 is a flowchart illustrating a control process according to the second embodiment. [Figure 13] 10 is a flowchart illustrating a control process according to the second embodiment. [Figure 14] FIG. 11 is a diagram illustrating an example of a system configuration according to a third embodiment. [Figure 15] 13A to 13C are diagrams illustrating examples of roles and contents that can be set in the image capture device of the third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, the embodiments will be described in detail with reference to the attached drawings. Note that the following embodiments do not limit the invention according to the claims. Although the embodiments describe a number of features, not all of these features are essential to the invention, and the features may be combined in any manner. Furthermore, in the attached drawings, the same reference numbers are used for the same or similar configurations, and duplicated descriptions are omitted.

[0012] [Embodiment 1] <System configuration> First, the system configuration of the first embodiment will be described with reference to FIG.

[0013] The system of this embodiment includes a first control device 100, a second control device 200, a first imaging device 300, and a second imaging device 400. In the system of this embodiment, the second imaging device 400 is controlled by either the first control device 100 or the second control device 200 to track a specific subject. In this embodiment, the specific subject is, for example, a person, but may also be an animal or an object.

[0014] The first control device 100 detects a subject to be tracked from an overhead image captured by the first imaging device 300, and controls the second imaging device 400 based on the detection result. The first control device 100 is also called a workstation. The subject to be tracked is set, for example, by a user operation or automatically.

[0015] The second control device 200 controls the second imaging device 400 based on the result of recognizing the subject of the tracking target from the overhead image captured by the first imaging device 300 and the result of recognizing the subject of the tracking target from the sub-image captured by the second imaging device 300. The second control device 200 is also called an edge box.

[0016] The first imaging device 300 has a fixed shooting angle of view at a wide angle, and can capture an overhead image including all of subjects A, B, and C. The first imaging device 300 is also called an overhead camera. The second imaging device 400 has a variable shooting angle of view, and can capture at least one of subjects A, B, and C. The second imaging device 400 is called a sub-camera. The first imaging device 300 and the second imaging device 400 are placed at positions separated from each other so that their shooting positions and / or shooting directions are different.

[0017] The first control device 100, the second control device 200, the first imaging device 300, and the second imaging device 400 are communicatively connected by a network 600 such as a LAN (Local Area Network). In this embodiment, an example in which the first control device 100, the second control device 200, the first imaging device 300, and the second imaging device 400 are connected by the network 600 will be described, but they may be connected by a connection cable (not shown). In this embodiment, an example in which there is one second imaging device 400 will be described, but there may be two or more. When there are multiple second imaging devices 400, a second control device 200 is provided for each second imaging device 400.

[0018] Next, the basic functions of the system of this embodiment will be described.

[0019] The first imaging device 300 captures an overhead image and transmits the overhead image to the first control device 100 via the network 600 .

[0020] The second imaging device 400 captures a sub-image including a subject to be tracked (tracked subject) and transmits the sub-image to the second control device 200 via the network 600. The second imaging device 400 has a PTZ function. The PTZ function is a function that can control pan, tilt, and zoom of the imaging device. PTZ is an abbreviation of the initial letters of pan, tilt, and zoom. Pan is the horizontal movement of the optical axis of the imaging device. Tilt is the vertical movement of the optical axis of the imaging device. Zoom is zoom up (telephoto) and zoom out (wide angle). Pan and tilt are functions that change the shooting direction of the imaging device. Zoom is a function that changes the shooting range (shooting angle of view) of the imaging device.

[0021] The first control device 100 determines a tracking subject from subjects detected from the overhead image received from the first imaging device 300, and calculates first feature information of the tracking subject from the overhead image. The first control device controls the second imaging device 400 to change the shooting direction and shooting range of the second imaging device 400 to the shooting direction and shooting range of the tracking subject based on the first feature information of the tracking subject.

[0022] After changing the shooting direction and shooting range of the second imaging device 400 to the shooting direction and shooting range of the tracked subject, the first control device 100 transmits first feature information of the tracked subject calculated from the overhead image to the second control device 200.

[0023] The second control device 200 detects a subject from the sub-image received from the second imaging device 400, and calculates second feature information of the detected subject. The second control device 200 compares the second feature information of the subject detected from the sub-image with the first feature information of the tracking subject received from the first control device 100.

[0024] When the similarity between the first feature information of the tracked subject and the second feature information of the subject detected from the sub-image is low, the first control device 100 controls the second imaging device 400 to change the shooting direction and shooting range of the second imaging device 400 to the shooting direction and shooting range of the tracked subject based on the first feature information of the tracked subject.

[0025] In addition, when there is a high degree of similarity between the first feature information of the tracked subject and the second feature information of the subject detected from the sub-image, the second control device 200 controls the second imaging device 400 to change the shooting direction and shooting range of the second imaging device 400 to the shooting direction and shooting range of the tracked subject based on the second feature information of the subject detected from the sub-image that has a high degree of similarity to the first feature information of the tracked subject.

[0026] The feature information is information that can identify that the same subject is captured by multiple imaging devices with different shooting positions and / or shooting directions. The feature information is an inference result that is output by performing image recognition by inference processing using a trained model on multiple images captured by multiple imaging devices with different shooting positions and / or shooting directions as input. When an inference result that the subjects are the same is obtained, it is possible to identify that the subjects included in the multiple images captured by the multiple imaging devices with different shooting positions and / or shooting directions are the same subject.

[0027] In the following description, the first control device 100 is referred to as a workstation (WS), the second control device 200 as an edge box (EB), the first imaging device 300 as an overhead camera, and the second imaging device 400 as a sub-camera.

[0028] <Device configuration> Next, the hardware configurations of the WS 100, the EB 200, the overhead camera 300, and the sub-camera 400 will be described in detail with reference to FIG.

[0029] First, the configuration of the WS 100 will be described.

[0030] The WS 100 includes a control unit 101, a volatile memory 102, a non-volatile memory 103, an inference unit 104, a communication unit 105, and an operation unit 106, and each unit is connected via an internal bus 110 so as to be able to send and receive data.

[0031] The control unit 101 has a processor (CPU) that performs arithmetic processing and control processing of the WS 100 , and controls each of the components of the WS 100 by executing a control program stored in the non-volatile memory 103 .

[0032] The volatile memory 102 is a main storage device such as a RAM. Constants and variables for the operation of the control unit 101, and control programs and inference programs read from the non-volatile memory 103 are loaded into the volatile memory 102. The volatile memory 102 also stores information such as image data and inference programs received from an external device by the communication unit 105. The volatile memory 102 also stores overhead image data received from the overhead camera 300. The volatile memory 102 has a sufficient storage capacity to hold this information.

[0033] The non-volatile memory 103 is an auxiliary storage device such as an EEPROM, a flash memory, a hard disk drive (HDD), a solid state drive (SSD), a memory card, etc. The non-volatile memory 103 stores an OS (operating system) which is basic software executed by the control unit 101, a control program including an application which cooperates with the OS to realize applied functions, an inference program used by the inference unit 104 for inference processing, etc.

[0034] The inference unit 104 executes an inference process using a learned inference model and inference parameters according to an inference program. The inference unit 104 executes an inference process to estimate the presence or absence and position of a specific object and feature information of the object from an overhead image received from the overhead camera 300. The inference process in the inference unit 104 can be executed by a calculation processing device specialized for image processing and inference process, such as a GPU (Graphics Processing Unit). The GPU is a processor capable of performing a large amount of product-sum calculations, and has a calculation processing capacity for performing matrix calculations of a neural network in a short time. The inference process in the inference unit 104 may be realized by a reconfigurable logic circuit such as an FPGA (Field-Programmable Gate Array). The inference process may be performed by the CPU and GPU of the control unit 101 working together, or by either the CPU or the GPU of the control unit 101.

[0035] The communication unit 105 is an interface (I / F) that complies with a wired communication standard such as Ethernet (registered trademark) or an interface that complies with a wireless communication standard such as Wi-Fi (registered trademark). The communication unit 105 is connected to external devices such as the EB 200, the overhead camera 300, and the sub-camera 400 via a network 600 such as a wired LAN or a wireless LAN, and can transmit and receive data to and from the external devices. The control unit 101 realizes communication with the external devices by controlling the communication unit 105. Note that the communication method is not limited to Ethernet (registered trademark) or Wi-Fi (registered trademark), and a communication standard such as IEEE1394 may also be used.

[0036] The operation unit 106 is an operation member such as various switches, buttons, a touch panel, etc. that receives various operations by the user and outputs operation information to the control unit 101. The operation unit 106 also provides a user interface for the user to operate the WS100.

[0037] The display unit 111 displays an overhead image, a subject recognition result, a GUI (Graphical User Interface) for interactive operations, etc. The display unit 111 is a display device such as a liquid crystal display or an organic EL display. The display unit 111 may be an integral part of the WS 100, or may be an external device connected to the WS 100.

[0038] Next, the configuration of the EB 200 will be described.

[0039] The EB 200 includes a control unit 201, a volatile memory 202, a non-volatile memory 203, an inference unit 204, and a communication unit 205, and each unit is connected via an internal bus 210 so as to be able to transmit and receive data.

[0040] The control unit 201 has a processor (CPU) that performs arithmetic processing and control processing of the EB 200, and controls each component of the EB 200 by executing a control program stored in the non-volatile memory 203.

[0041] The volatile memory 202 is a main storage device such as a RAM. Constants and variables for the operation of the control unit 201, and control programs and inference programs read from the non-volatile memory 203 are loaded into the volatile memory 202. The volatile memory 202 also stores information such as image data and inference programs received from an external device by the communication unit 205. The volatile memory 202 also stores sub-image data received from the sub-camera 400. The volatile memory 202 has a sufficient storage capacity to hold this information.

[0042] The non-volatile memory 203 is an auxiliary storage device such as an EEPROM, a flash memory, a hard disk drive (HDD), a solid state drive (SSD), a memory card, etc. The non-volatile memory 203 stores an OS (operating system) which is basic software executed by the control unit 201, a control program including an application which cooperates with the OS to realize applied functions, an inference program used by the inference unit 204 for inference processing, etc.

[0043] The inference unit 204 executes an inference process using a learned inference model and inference parameters according to an inference program. The inference unit 204 executes an inference process to estimate the presence or absence and position of a specific object, and feature information of the object, from a sub-image received from the sub-camera 400. The inference process in the inference unit 204 can be executed by a calculation processing device specialized for image processing and inference process, such as a GPU (Graphics Processing Unit). The GPU is a processor capable of performing a large amount of product-sum calculations, and has a calculation processing capability for performing matrix calculations of a neural network in a short time. The inference process in the inference unit 204 may be realized by a reconfigurable logic circuit, such as an FPGA (Field-Programmable Gate Array). The inference process may be performed by a CPU and a GPU of the control unit 201 working together, or by either the CPU or the GPU of the control unit 201.

[0044] The communication unit 205 is an interface (I / F) that complies with a wired communication standard such as Ethernet (registered trademark) or an interface that complies with a wireless communication standard such as Wi-Fi (registered trademark). The communication unit 205 is connected to external devices such as the WS 100 and the sub-camera 400 via a network 600 such as a wired LAN or a wireless LAN, and can transmit and receive data to and from the external devices. The control unit 201 realizes communication with the external devices by controlling the communication unit 205. Note that the communication method is not limited to Ethernet (registered trademark) or Wi-Fi (registered trademark), and a communication standard such as IEEE1394 may also be used.

[0045] Next, the configuration of the overhead camera 300 will be described.

[0046] The overhead camera 300 includes a control unit 301, a volatile memory 302, a non-volatile memory 303, a communication unit 305, an imaging unit 306, and an image processing unit 307, and each unit is connected via an internal bus 310 so as to be able to send and receive data.

[0047] The control unit 301 performs overall control of the overhead camera 300 under the control of the WS 100. The control unit 301 has a processor (CPU) that performs calculation processing and control processing of the overhead camera 300, and controls each component of the overhead camera 300 by executing a control program stored in the non-volatile memory 303.

[0048] Volatile memory 302 is a main storage device such as a RAM. Constants and variables for the operation of control unit 301, and control programs and inference programs read from non-volatile memory 303 are loaded into volatile memory 302. Volatile memory 302 also stores overhead image data captured by imaging unit 306 and processed by image processing unit 307. Volatile memory 302 has a sufficient storage capacity to hold this information.

[0049] The non-volatile memory 303 is an auxiliary storage device such as an EEPROM, a flash memory, a hard disk drive (HDD), a solid state drive (SSD), a memory card, etc. The non-volatile memory 303 stores an OS (operating system) which is basic software executed by the control unit 301, and a control program including an application which cooperates with the OS to realize practical functions.

[0050] The imaging unit 306 has an image sensor composed of a CCD (charge-coupled device), a CMOS (complementary metal-oxide semiconductor) element, etc., and converts an optical image of a subject into an electrical signal. In this embodiment, the overhead camera 300 has a fixed shooting angle of view so that an overhead image including a plurality of subjects including a tracking subject can be captured.

[0051] The image processing unit 307 performs various image processing on image data output from the imaging unit 306 or image data read from the volatile memory 302. The various image processing includes, for example, image processing such as noise removal, edge emphasis, and enlargement / reduction, image correction processing such as contrast correction, brightness correction, and color correction, and trimming or cropping processing for cutting out a part of the image data. The image processing unit 307 converts the image data that has been subjected to the image processing into an image file in a predetermined format (for example, JPEG) and records it in the non-volatile memory 303. In addition, the image processing unit 307 performs predetermined calculation processing using the image data, and the control unit 301 performs AF (autofocus) processing and AE (autoexposure) processing based on the calculation results.

[0052] The communication unit 305 is an interface (I / F) that complies with a wired communication standard such as Ethernet (registered trademark) or an interface that complies with a wireless communication standard such as Wi-Fi (registered trademark). The communication unit 305 can connect to an external device such as WS100 via a network 600 such as a wired LAN or wireless LAN, and transmit and receive data to and from the external device. The control unit 301 realizes communication with the external device by controlling the communication unit 305. Note that the communication method is not limited to Ethernet (registered trademark) or Wi-Fi (registered trademark), and a communication standard such as IEEE1394 may also be used.

[0053] Next, the configuration of the sub-camera 400 will be described.

[0054] The sub-camera 400 comprises a control unit 401, a volatile memory 402, a non-volatile memory 403, a communication unit 405, an imaging unit 406, an image processing unit 407, an optical unit 408 and a PTZ drive unit 409, and each unit is connected via an internal bus 410 so as to be able to send and receive data.

[0055] The control unit 401 performs overall control of the sub-camera 400 under the control of the WS 100 or the EB 200. The control unit 401 has a processor (CPU) that performs arithmetic processing and control processing of the sub-camera 400, and controls each component of the sub-camera 400 by executing a control program stored in the non-volatile memory 403.

[0056] The volatile memory 402 is a main storage device such as a RAM. Constants and variables for the operation of the control unit 401, and control programs and inference programs read from the non-volatile memory 403 are loaded into the volatile memory 402. The volatile memory 402 also stores overhead image data captured by the imaging unit 406 and processed by the image processing unit 407. The volatile memory 402 has a sufficient storage capacity to hold this information.

[0057] The non-volatile memory 403 is an auxiliary storage device such as an EEPROM, a flash memory, a hard disk drive (HDD), a solid state drive (SSD), a memory card, etc. The non-volatile memory 403 stores an OS (operating system) which is basic software executed by the control unit 401, and a control program including an application which cooperates with the OS to realize practical functions.

[0058] The imaging unit 406 has an image sensor configured with a CCD (charge-coupled device), a CMOS (complementary metal-oxide semiconductor) element, or the like, and converts an optical image of a subject into an electrical signal.

[0059] The image processing unit 407 executes various image processing on image data output from the imaging unit 406 or image data read from the volatile memory 402. The various image processing includes, for example, image processing such as noise removal, edge emphasis, and enlargement / reduction, image correction processing such as contrast correction, brightness correction, and color correction, and trimming or cropping processing for cutting out a part of the image data. The image processing unit 407 converts the image data that has been subjected to image processing into an image file in a predetermined format (for example, JPEG) and records it in the non-volatile memory 403. In addition, the image processing unit 407 executes predetermined calculation processing using the image data, and the control unit 401 executes AF (autofocus) processing and AE (autoexposure) processing based on the calculation result.

[0060] The communication unit 405 is an interface (I / F) that complies with a wired communication standard such as Ethernet (registered trademark) or an interface that complies with a wireless communication standard such as Wi-Fi (registered trademark). The communication unit 405 can connect to an external device such as the EB 200 via a network 600 such as a wired LAN or wireless LAN, and can transmit and receive data to and from the external device. The control unit 401 realizes communication with the external device by controlling the communication unit 405. Note that the communication method is not limited to Ethernet (registered trademark) or Wi-Fi (registered trademark), and a communication standard such as IEEE1394 may also be used.

[0061] The optical unit 408 includes a lens group including a zoom lens and a focus lens, a shutter with an aperture function, and a mechanism for driving these optical members. The optical unit 408 drives the optical members to at least one of rotate the shooting direction of the sub-camera 400 around the pan (P) axis (horizontal direction) or the tilt (T) axis (vertical direction), and change the shooting range (shooting angle of view) of the sub-camera 400 along the zoom (Z) axis (enlargement / reduction direction).

[0062] The PTZ driving unit 409 includes actuators such as mechanical elements and motors for driving the optical unit 408 in the PTZ direction, and drives the optical unit 408 in the PTZ direction under the control of the control unit 401 .

[0063] Note that the zoom function of this embodiment is not limited to optical zoom, which changes the focal length by moving a zoom lens, but may be digital zoom, which cuts out and enlarges a portion of the captured image data, or a combination of optical zoom and digital zoom.

[0064] [Control process] Next, with reference to Figures 3 to 10, a control process for tracking a tracking subject by switching between a mode in which WS100 controls the sub-camera 400 based on an overhead image and a mode in which EB200 controls the sub-camera 400 based on a sub-image will be described.

[0065] First, the functional configuration of the WS 100 and the EB 200 for implementing the control process of this embodiment will be described with reference to FIGS.

[0066] Each function of the WS 100 and the EB 200 is realized by hardware and / or software. If the functional units shown in Fig. 3 are configured by hardware instead of by software, it is sufficient to have a circuit configuration corresponding to each functional unit in Fig. 3.

[0067] The WS 100 includes an image recognition unit 121, an object of interest determination unit 122, a tracking target determination unit 123, a control information generation unit 124, a feature information determination unit 125, and a tracking state determination unit 126. Software for realizing these functions is stored in the non-volatile memory 103, and the control unit 101 loads it into the volatile memory 102 and executes it.

[0068] The EB 200 includes an image recognition unit 221, a tracking target determination unit 222, and a control information generation unit 223. These pieces of software are stored in the non-volatile memory 203, and the control unit 201 loads them into the volatile memory 202 and executes them.

[0069] Fig. 4(a) is a flowchart showing the basic operation of the WS 100. Fig. 4(b) is a flowchart showing the basic operation of the EB 200. Fig. 4(c) is a flowchart showing the operation of the overhead camera 300. Fig. 4(d) is a flowchart showing the operation of the sub-camera 400.

[0070] First, the software functions and basic operations of the WS 100 will be described with reference to FIG. 3 and FIG.

[0071] In step S101, the control unit 101 transmits a shooting command to the overhead camera 300 using a predetermined protocol via the communication unit 105, receives an overhead image from the overhead camera 300, stores it in the volatile memory 102, and advances the process to step S102.

[0072] In step S102, the control unit 101 executes the function of the image recognition unit 121 in FIG. 3, and advances the process to step S103.

[0073] The image recognition unit 121 controls the inference unit 104, the volatile memory 102, and the non-volatile memory 103, and performs the following object recognition process.

[0074] The image recognition unit 121 receives the overhead image IMG of the overhead camera 300 read from the volatile memory 102 and reference position information REF_POSI of the overhead camera 300. The position information REF_POSI of the overhead camera 300 includes information on the position of the overhead camera 300 and marker coordinates. The image recognition unit 121 detects the subject and calculates feature information based on the overhead image IMG of the overhead camera 300 and the reference position information REF_POSIREF_POSI. The image recognition unit 121 then outputs coordinate information POSITION[n] indicating the position of the detected subject, ID[n] indicating identification information of the detected subject, and STAT[n] indicating feature information of the detected subject. The position of the overhead camera 300 is a position in a coordinate space in which the shooting area of ​​the overhead camera 300 is viewed from directly above, and is known in advance by being measured by a user operation or using a sensor (not shown). The marker coordinates are position information of a marker installed in a coordinate space in which the shooting area of ​​the overhead camera 300 is viewed from directly above in order to calculate a homography transformation matrix described later, and are known values ​​measured in advance manually or using a sensor (not shown). The marker is like a mark having a color different from the color of the floor or ground, and may be any type as long as it can be measured by a user operation or a sensor (not shown). For example, if the sensor (not shown) is a camera, the marker position is obtained by extracting the color of the marker from an image captured with the marker marked with an arbitrary color. The position and marker coordinates of the overhead camera 300 may be input by the user via the operation unit 106 of the WS 100, and the control unit 101 may store them in the volatile memory 102. The reference position information REF_POSI and the coordinate information POSITION[n] of the subject are expressed in a coordinate system converted into a coordinate space in which the shooting area of ​​the overhead camera 300 is viewed from directly above. n is an index indicating the number of subjects detected, and for example, when the inference unit 104 detects three people, the POSITION, ID, and STAT for the three people are output as the inference result. The control unit 101 stores the subject recognition result by the image recognition unit 121 in the volatile memory 102. The subject detection process and the feature information calculation process will be described in detail later.

[0075] Here, a method for calculating the subject coordinate information POSITION by the image recognition unit 121 will be described.

[0076] First, with reference to FIG. 5, the relationship between the coordinate system of the overhead image of the overhead camera 300 and the coordinate system when the shooting area of ​​the overhead camera 300 is viewed from directly above will be described.

[0077] In order to calculate a pan value such that the shooting direction of the sub camera 400 is the direction of the tracking subject, the calculation is simplified by calculating the angle in a plane coordinate space perpendicular to the axis along which the sub camera 400 performs the panning operation. For example, when the sub camera 400 is installed perpendicular to a ground surface (reference position) such as a floor or the ground, the coordinate space perpendicular to the axis along which the sub camera 400 performs the panning operation is a coordinate space parallel to the reference position (a coordinate space in which the space in which the sub camera 400 and the subject are present is viewed from directly above) as shown in FIG. 5(b). In this embodiment, the sub camera 400 is assumed to be installed perpendicular to the reference position, and the pan value is calculated in a coordinate system in which the shooting area of ​​the overhead camera 300 is viewed from directly above. That is, the subject position detected in the coordinate system of the overhead image of the overhead camera 300 shown in FIG. 6(a) (hereinafter, overhead camera coordinate system) is converted to a coordinate system in which the shooting area of ​​the overhead camera 300 is viewed from directly above (hereinafter, plane coordinate system) shown in FIG. 5(b). The coordinate transformation is performed using the homography transformation matrix H according to the following formula 1. (Formula 1) TIFF2025038870000002.tif19155In Equation 1, x and y are the horizontal and vertical coordinates in the overhead camera coordinate system, and X and Y are the horizontal and vertical coordinates in the plane coordinate system.

[0078] The control unit 101 reads out the reference position information REF_POSI from the volatile memory 102, and substitutes the marker coordinates Mark_A to Mark_D shown in FIGS. 5(a) and 5(b) included in the reference position information REF_POSI into Equation 1 to calculate the homography transformation matrix H. The marker coordinates are values ​​in a planar coordinate system. By using Equation 1, any coordinate in the overhead camera coordinate system of FIG. 5(a) can be mapped to any coordinate in the planar coordinate system of FIG. 5(b). In the example of FIG. 5, the control unit 101 can grasp the positions of the subjects A, B, and C included in the overhead image IMG of the overhead camera 300 in the planar coordinate system of FIG. 5(b). The control unit 101 stores the homography transformation matrix H calculated by the above Equation 1 in the volatile memory 102.

[0079] Next, a method for detecting the subject position using an inference model for subject detection and a method for converting the subject position into a planar coordinate system will be described.

[0080] In this embodiment, subject detection is performed by performing image recognition processing using a trained inference model for subject detection that has been created by performing machine learning such as deep learning.

[0081] The inference model for subject detection receives an overhead image as input and outputs coordinate information on the image of the subject contained in the overhead image.

[0082] The control unit 101 detects a subject by performing image recognition processing using an inference model for subject detection using the overhead image IMG of the overhead camera 300 as input by the inference unit 104. FIG. 6(a) shows an example in which a subject detected by the inference unit 104 is displayed in a rectangular frame. As shown in FIG. 6(a). As shown in FIG. 6(a), the coordinates of a rectangular portion circumscribing the subject A, subject B, and subject C detected from the overhead image are detected as the subject position. The control unit 101 stores the coordinate information of the subject detected from the overhead image in the volatile memory 102. Note that, in this embodiment, an example of subject detection by inference processing using a trained model has been described, but is not limited to this. For example, a method called the SIFT method, which detects by matching local feature points in an image, or a method called a template matching method, which detects by calculating the similarity with a template image, may be used.

[0083] Furthermore, the control unit 101 converts the lower end of the rectangular part of the subject detected in the overhead camera coordinate system shown in FIG. 6(a) into the planar coordinate system shown in FIG. 6(b) as the subject detection position (the person's foot coordinates in the example of FIG. 6). For example, the control unit 101 reads out the homography transformation matrix H from the volatile memory 102 and substitutes the foot coordinates (xa, ya) of the subject A in the overhead camera coordinate system into x and y in Equation 1, thereby making it possible to convert the foot coordinates (XA, YA) in the planar coordinate system. Similarly, for the foot coordinates (xb, yb) of the subject B and the foot coordinates (xc, yc) of the subject C, it becomes possible to calculate the foot coordinates (XB, YB) of the subject B and the foot coordinates (XC, YC) of the subject C in the planar coordinate system. The control unit 101 writes the foot coordinates into the volatile memory 102 as the subject's position coordinates POSITION.

[0084] Next, a method for generating subject identification information ID and feature information STAT by image recognition unit 121 will be described.

[0085] The control unit 101 inputs the subject coordinate information POSITION, which is the inference result of the inference model for subject detection, and the overhead image of the overhead camera 300 into the learned inference model for subject identification created by machine learning such as deep learning using the inference unit 104, and outputs identification information ID and feature information STAT by performing inference processing. The inference model for subject identification is different from the inference model for subject detection.

[0086] Here, we will explain the inference model for subject identification.

[0087] The inference model for identifying a subject in this embodiment is a trained model that has been trained to increase the similarity of feature information for images of the same subject using training data that is a collection of data as many as the number of subjects that associate a set of images of a specific subject taken from multiple different shooting directions with information that can identify the specific subject. Feature information STAT is output by inputting an image of the subject cut out based on the coordinate position POSITION of the subject, which is the output of the inference model for detecting the subject, into the inference model for identifying the subject. When an image of the same subject taken by a different camera is input, the output feature information has a higher similarity to the feature information STAT compared to when an image of a different subject is input. Examples of feature information include a multidimensional vector of the response of the convolution layer of a convolutional neural network. Similarity will be described later.

[0088] The inference model for subject detection and the inference model for subject identification are stored in the non-volatile memory 103 before the control process of this embodiment is started.

[0089] Moreover, the image recognition unit 121 assigns identification information ID of the subject corresponding to the feature information which is the inference result of the inference model for identifying the subject. Furthermore, the image recognition unit 121 calculates the similarity of the feature information of each image of the subject obtained by inputting the image of each subject detected by the inference model for detecting the subject using each image of the current frame and the past frame as input into the inference model for identifying the subject. The similarity is calculated using cosine similarity. The cosine similarity is closer to 1 as the multidimensional vector which is the feature information of each subject image is more similar, and closer to 0 as the multidimensional vector is more different. The same ID is assigned to the subject having the closest similarity between the past frame and the current frame. Note that the method of calculating the similarity is not limited to this, and any method may be used as long as it outputs a higher value as the feature information is closer, and outputs a lower value as the feature information is further away. Note that, in this embodiment, the feature information is used to assign the ID, but this is not limited to this. A method may be used in which the position and size of the rectangular information of the detected subject are compared using the rectangular information of the subject obtained by the inference model for detecting the subject between the current frame and the past frame, and the same ID is assigned to the closest subject. Alternatively, the position of the rectangular information in the current frame may be predicted from the transition of the position of the rectangular information for the same ID in the past few frames using a Kalman filter or the like, and the same ID may be assigned to the subject that is closest to the predicted position of the rectangular information. IDs may also be assigned using a combination of these methods. By using such a method, the accuracy of ID assignment can be improved when a subject with a similar appearance suddenly enters the shooting angle of view.

[0090] As described above, the image recognition unit 121 performs inference processing using an inference model for subject detection with the overhead image of the overhead image 300 as input, outputs the coordinate position POSITION of the subject, and stores it in the volatile memory 102. The image recognition unit 121 also inputs the subject coordinate information POSITION, which is the inference result of the inference model for subject detection, and the overhead image of the overhead camera 300 to an inference model for subject identification to perform inference processing. Then, the image recognition unit 121 outputs the identification information ID and feature information STAT as the result of the inference processing, and stores it in the volatile memory 102.

[0091] Returning to the description of FIG. 4, in step S103, the control unit 101 executes the function of the target subject determination unit 122 in FIG. 3, and advances the process to step S104.

[0092] The target subject determining unit 122 determines a target subject MAIN_SUBJECT from operation information input by the user via the operation unit 106 and coordinate information of the subject, which is the subject recognition result by the image recognition unit 121 read from the volatile memory 102 .

[0093] The control unit 101 displays the overhead image captured by the overhead camera 300 and the subject recognition results in the volatile memory 102 on the display unit 111 of the WS 100. The control unit 101 allows the user to select a subject of interest from among the subjects displayed as subject recognition results via the operation unit 106. For example, if the operation unit 106 is a mouse, the user can click and select one of the subjects displayed on the display unit 111. The control unit 101 saves the identification information ID corresponding to the subject of interest selected by the user in the volatile memory 102 as the subject of interest MAIN_SUBJECT.

[0094] In step S104, the control unit 101 executes the function of the tracking target determination unit 123 in FIG. 3, and advances the process to step S105.

[0095] The tracking target determining unit 123 determines a tracking subject SUBJECT_ID of the sub camera 400 from the target subject MAIN_SUBJECT determined by the target subject determining unit 122 .

[0096] Here, a method for determining a subject to be tracked by the sub camera 400 will be described.

[0097] The control unit 101 reads out the target subject MAIN_SUBJECT determined by the target subject determination unit 122 from the volatile memory 102, and determines the target subject MAIN_SUBJECT as the tracking subject SUBJECT_ID of the sub camera 400. In this way, by setting the same subject as the target subject MAIN_SUBJECT selected by the user as the tracking subject SUBJECT_ID of the sub camera 400, it is possible to control the sub camera 400 with the subject selected by the user as the tracking target.

[0098] The method of determining the tracking subject is not limited to the above method, and may be determined using information on the target subject MAIN_SUBJECT and identification information ID read from the volatile memory 102, for example. For example, when multiple subjects are included in the overhead image of the overhead camera 300 and multiple sub cameras 400 are installed, one sub camera may track the same subject as the target of interest, and another sub camera may track a different subject from the target of interest. By determining the tracking subject in this way, multiple subjects included in the overhead image of the overhead camera 300 can be tracked comprehensively for each sub camera. In addition, there is also a method of reading out the coordinate information POSITION, identification information ID, and REF_POSI including the sub camera position of the subject from the volatile memory 102, and determining the subject closest to the sub camera as the tracking subject among the subjects detected from the overhead image of the overhead camera 300. By determining the tracking subject in this way, the subject that is easiest to fit in the angle of view from the position of the sub camera can be set as the tracking subject. The control unit 101 stores the tracking subject SUBJECT_ID determined as described above in the volatile memory 102, and also stores the identification ID of the tracking subject before it was stored in the volatile memory 102 as a past tracking subject ID.

[0099] In step S105, the control unit 101 executes the function of the feature information determination unit 125 to transmit feature information corresponding to the tracking subject of the sub camera 400 to the EB 200. In addition, the control unit 101 executes the function of the tracking state determination unit 126 to update the tracking state information STATE, store it in the volatile memory 102, and proceeds to step S106.

[0100] The tracking state information STATE includes any one of the following information: "Tracking by WS100" and "Tracking by EB200". "Tracking by WS100" indicates a state in which WS100 is tracking a tracking subject by controlling the sub-camera 400. "Tracking by EB200" indicates a state in which EB200 is tracking a tracking subject by controlling the sub-camera 400. The process of step S105 will be described later in detail.

[0101] In step S106, the control unit 101 reads the tracking state information STATE from the volatile memory 102, and determines whether "tracking by WS100" or "tracking by EB200" based on the tracking state information STATE. If the control unit 101 determines that "tracking by WS100" is true, the process proceeds to step S107, and if the control unit 101 determines that "tracking by EB200" is true, the process returns to step S101.

[0102] In step S107, the control unit 101 executes the function of the control information generating unit 124 in FIG. 3, and the process proceeds to step S108.

[0103] The control information generating unit 124 calculates pan / tilt values ​​PT_VALUE of the sub camera 400 for tracking the tracking subject SUBJECT_ID determined by the tracking target determining unit 123 by the sub camera 400. The control unit 101 reads out coordinate information of the sub camera 400 in a planar coordinate system included in the reference position information REF_POSI and coordinate information POSITION of the detected subject from the volatile memory 102. Then, the control unit 101 calculates pan / tilt values ​​such that the shooting direction of the sub camera 400 is the direction of the tracking subject from the coordinate information of the subject corresponding to the tracking subject SUBJECT_ID.

[0104] Here, a method for calculating the pan value will be described with reference to FIG.

[0105] As shown in FIG. 7, the angle θ between a line extending from the center of the optical axis of the sub-camera 400 and a line connecting the sub-camera 400 and the tracking subject SUBJECT_ID can be calculated by the following formula 2. (Formula 2) TIFF2025038870000003.tif19155 In Equation 2, px and py are the horizontal and vertical coordinates of the position of the tracked subject, and subx and suby are the horizontal and vertical coordinates of the position of the sub-camera 400. px and py can be found from the coordinate information POSITION of the detected subject by referring to the coordinate information corresponding to the tracked subject SUBJECT_ID.

[0106] The control information generator 124 calculates the pan value of the sub camera 400 based on the angle θ.

[0107] Next, a method for calculating the tilt control value will be described with reference to FIG.

[0108] As shown in FIG. 8, the height h1 of the optical axis of the sub-camera 400 is taken as the angle ρ between a line extending from the center of the optical axis of the sub-camera 400 and a line extending toward the height h2 of a specific part of the tracked subject (in the case of a person, the height of the face), and the angle ρ can be calculated using the following equations 3 and 4. (Formula 3) TIFF2025038870000004.tif13155 (Formula 4) TIFF2025038870000005.tif19155 In formula 4, h1 is the height of the sub-camera 400 from the ground surface, and h2 is the height from the ground surface to a predetermined part of the tracking subject (in the case of a person, the face). h1 and h2 may be stored in the volatile memory 102 in advance, or may be measured in real time using a sensor (not shown).

[0109] The control information generator 124 calculates a tilt control value for the sub camera 400 based on the angle ρ.

[0110] The pan value / tilt value may be a speed value for directing the sub camera 400 toward the tracking subject. The method of calculating the pan value / tilt value is as follows: first, the control unit 101 acquires the current pan value / tilt value of the sub camera 400 from the EB 200. Next, the control unit 101 calculates a pan angular velocity proportional to the difference with the pan value θ read from the volatile memory 102. The control unit 101 also calculates a tilt angular velocity proportional to the difference with the tilt control value ρ read from the volatile memory 102. Then, the control unit 101 stores the calculated control value in the volatile memory 102.

[0111] In step S108, the control unit 101 reads the pan value / tilt value from the volatile memory 102, converts them into control commands according to a predetermined protocol for controlling the sub camera 400, stores them in the volatile memory 102, and proceeds to step S109.

[0112] In step S109, the control unit 101 transmits a control command according to the pan value / tilt value calculated in step S108 to the sub-camera 400 via the communication unit 105, and returns the process to step S101.

[0113] The above is the basic operation of the WS100.

[0114] Next, the function and basic operation of the EB 200 will be described with reference to FIG. 3 and FIG. 4(b).

[0115] In step S201, the control unit 201 transmits a shooting command to the sub-camera 400 via the communication unit 205, receives a captured sub-image from the sub-camera 400, stores the captured sub-image in the volatile memory 202, and advances the process to step S202.

[0116] In step S202, the control unit 201 executes the function of the image recognition unit 221 in FIG. 3, and advances the process to step S203.

[0117] The image recognition unit 221 has the same functions as the image recognition unit 121 of the WS 100. The control unit 201 inputs the sub-image of the sub-camera 400 read from the volatile memory 202 by the inference unit 204 into a trained model created by performing machine learning such as deep learning, and performs inference processing. The inference result includes coordinate information POSITION of the subject detected from the sub-image of the sub-camera 400, feature information STAT_SUB[m], and identification information ID for each subject, and is stored in the volatile memory 202. Note that the trained model used for the inference processing of the image recognition unit 221 is a common model (inference model for subject detection, inference model for subject identification) with the trained model used by the image recognition unit 121 of the WS 100.

[0118] In step S203, the control unit 201 receives the feature information STAT of the subject from the WS 100 via the communication unit 205, and compares it with the feature information STAT_SUB calculated from the sub-image of the sub-camera 400 using the function of the tracking target determination unit 222 in FIG. If a subject having a high similarity between the feature information STAT and the feature information STAT_SUB is present within the shooting angle of view of the sub camera 400, the identification information ID of the subject is determined as the identification information ID of the subject to be tracked by the sub camera 400=SUBJECT_ID, and is stored in the volatile memory 102, and the process proceeds to step S204. The method of calculating the similarity will be described in detail later.

[0119] In step S204, the control unit 201 checks the communication state for the WS 100 to stop tracking or continue tracking via the communication unit 205, performs processing according to the communication content, and proceeds to step S205. The processing in step S204 will be described in detail later.

[0120] In step S205, the control unit 201 determines whether or not information on the SUBJECT_ID of the tracking subject is stored in the volatile memory 202. If the control unit 201 determines that information on the SUBJECT_ID of the tracking subject is stored in the volatile memory 202, that is, that the identification information ID of the tracking subject of the sub camera 400 is stored in the volatile memory 102, the process proceeds to step S206. If the control unit 201 determines that information on the SUBJECT_ID of the tracking subject is not stored in the volatile memory 202, that is, that the identification information ID of the tracking subject of the sub camera 400 is not stored in the volatile memory 102, the process returns to step S201.

[0121] In step S206, the control unit 201 reads out the identification information ID for each subject, which is the subject recognition result in step S202, from the volatile memory 202, and determines whether or not the tracking subject SUBJECT_ID exists in the sub-image of the sub-camera 400. If the control unit 201 determines that the tracking subject SUBJECT_ID exists in the sub-image, the process proceeds to step S207, and if it determines that the tracking subject SUBJECT_ID does not exist, the process returns to step S201.

[0122] In step S207, the control unit 101 executes the function of the control information generating unit 223 in FIG. 3, and proceeds to step S208.

[0123] The control information generating unit 223 has a function of calculating the pan value / tilt value of the sub camera 400. The control unit 201 reads out the subject coordinate information POSITION and the tracking subject SUBJECT_ID from the volatile memory 202, and specifies the current position of the tracking subject corresponding to the tracking subject SUBJECT_ID. The control unit 201 reads out the past positions of the tracking subject within the shooting angle of view from the volatile memory 202, and calculates the angular velocity of the pan to be larger if there is a large difference in the horizontal direction between the current position of the tracking subject and the past position of the tracking subject, and calculates the angular velocity of the tilt to be larger if there is a large difference in the vertical direction. The control unit 201 saves the pan value / tilt value in the volatile memory 202.

[0124] In step S208, the control unit 201 converts the pan / tilt values ​​read from the volatile memory 202 into control commands in accordance with a predetermined protocol for controlling the sub-camera 400, stores the control commands in the volatile memory 202, and proceeds to step S209.

[0125] In step S209, the control unit 201 transmits a control command corresponding to the pan value / tilt value calculated in step S208 to the sub-camera 400 via the communication unit 205, and returns the process to step S101.

[0126] The above is the basic operation of the EB200.

[0127] As described above, WS100 performs image recognition processing on the overhead image of overhead camera 300, and controls the panning / tilting operations of sub camera 400 when tracking state information STATE is "tracking by WS100". When tracking state information STATE is "tracking by EB200", WS100 does not control the panning / tilting operations of sub camera 400. EB200 performs image recognition processing on the sub image of sub camera 400, and controls the panning / tilting operations of sub camera 400 when a tracking subject is set and detected from the sub image. When a tracking subject is not set, EB200 does not control the panning / tilting operations of sub camera 400. In addition, by updating the tracking state information STATE and the setting of the tracking subject through a control process described later in FIG. 9, it becomes possible to switch between WS100 and EB200 to control sub camera 400. In addition, the pan / tilt values ​​are transmitted only by one of the devices controlling the sub-camera 400, and are not transmitted when the other device is in control, thereby making it possible to reduce the amount of communication compared to the case where the pan / tilt values ​​are transmitted for each process in Figures 4(a) and (b).

[0128] Next, the operation of the overhead camera 300 when a shooting command is received from the WS 100 will be described with reference to FIG.

[0129] In step S301, the control unit 301 receives a shooting command from the WS 100 via the communication unit 305, and the process proceeds to step S302.

[0130] In step S302, the control unit 301 starts an image capturing process in response to receiving an image capturing command via the communication unit 305, and proceeds to step S303. The control unit 301 captures an image using the imaging unit 306, and stores the generated image data in the volatile memory 302 after performing predetermined image processing using the image processing unit 307.

[0131] In step S 303 , the control unit 301 reads the image data from the volatile memory 302 , and transmits it to the WS 100 via the communication unit 305 .

[0132] The operation of the overhead camera 300 has been described above.

[0133] Next, the operation of the sub-camera 400 that receives a control command from the WS 100 or the EB 200 will be described with reference to FIG.

[0134] In step S401, the control unit 401 receives a control command via the communication unit 405, stores the control command in the volatile memory 402, and advances the process to step S402.

[0135] In step S402, the control unit 401 reads out the pan / tilt values ​​from the volatile memory 402 in response to receiving a control command from the communication unit 405, and advances the process to step S403.

[0136] In step S403, the control unit 401 calculates drive parameters for controlling the pan operation / tilt operation at a desired speed in a desired direction based on the pan value / tilt value read from the nonvolatile memory 403, and proceeds to step S404. The drive parameters are parameters for controlling the actuators for the pan / tilt directions included in the PTZ drive unit 409, and the pan value / tilt value included in the control command is converted into the drive parameters by referring to a conversion table stored in the nonvolatile memory 403.

[0137] In step S404, the control unit 401 controls the optical unit 408 by the PTZ driving unit 409 based on the driving parameters obtained in step S403, and changes the shooting direction of the sub camera 400. The PTZ driving unit 409 changes the shooting direction of the sub camera 400 by driving the optical unit 408 in the pan / tilt direction based on the driving parameters.

[0138] The operation of the sub-camera 400 has been described above.

[0139] Next, the control process of the WS 100 will be described with reference to FIG.

[0140] FIG. 9(a) shows the control process of the WS 100, and shows the detailed process of step S105 in FIG. 4(a).

[0141] Part of the processing in FIG. 9(a) is realized by the control unit 101 executing the function of the tracking state determination unit 126 in FIG.

[0142] The tracking state determination unit 126 has a function of updating the tracking state information STATE stored in the volatile memory 102 .

[0143] In step S110, the control unit 101 reads out from the volatile memory 102 the SUBJECT_ID of the tracking subject of the sub camera 400 calculated in step S104 in Fig. 4A and the identification information ID indicating the previous tracking subject. Then, the control unit 101 compares the identification information read out from the volatile memory 102 to determine whether or not the tracking subject of the sub camera 400 has changed. If the control unit 101 determines that the tracking subject of the sub camera 400 has changed, the process proceeds to step S111, and if the control unit 101 determines that the tracking subject has not changed, the process proceeds to step S113.

[0144] In step S111, the control unit 101 transmits a tracking stop command to the EB 200 via the communication unit 105, and the process proceeds to step S112.

[0145] In step S112, the control unit 101 executes the function of the tracking state determination unit 126 in FIG. 3, and changes the tracking state information STATE to "tracking by WS 100".

[0146] When the tracking subject of the sub camera 400 is changed, there is a high possibility that the tracking subject is not present within the shooting angle of view of the sub camera 400. In this case, by performing the processes of steps S111 and S112, the WS 100 controls the sub camera 400 based on the overhead image of the overhead camera 300 instead of the sub camera 400.

[0147] In step S113, the control unit 101 reads the tracking state information STATE from the volatile memory 102, and determines whether "tracking by WS100" or "tracking by EB200" based on the tracking state information STATE. If the control unit 101 determines that "tracking by WS100" is true, the process proceeds to step S117, and if the control unit 101 determines that "tracking by EB200" is true, the process proceeds to step S114.

[0148] In step S114, the control unit 101 transmits a tracking continuation confirmation request to the EB200 via the communication unit 105, and inquires whether the EB200 can continue tracking the tracked subject. The response from the EB200 is "Continue tracking OK" or "Continue tracking NG." If the control unit 101 receives a notification of "Continue tracking OK" from the EB200, the process returns to step S101, and if the control unit 101 receives a notification of "Continue tracking NG" from the EB200, the process proceeds to step S115.

[0149] In step S115, the control unit 101 transmits a tracking stop command to the EB 200 via the communication unit 105, and the process proceeds to step S116.

[0150] In step S116, the control unit 101 executes the function of the tracking state determination unit 126 in FIG. 3, updates the tracking state information STATE to "tracking by WS 100", and ends the process.

[0151] By performing the processes from steps S114 to S116, when the tracking state is "tracking by EB200", tracking can be continued by WS100 even if the EB200 becomes unable to perform tracking.

[0152] In step S117, the control unit 101 determines whether or not the tracking subject is present within the shooting angle of view of the sub camera 400. If the control unit 101 determines that the tracking subject is present within the shooting angle of view of the sub camera 400, the control unit 101 advances the process to step S118. If the control unit 101 determines that the tracking subject is not present within the shooting angle of view of the sub camera 400, the control unit 101 ends the process. Whether or not the tracking subject is present within the shooting angle of view of the sub camera 400 can be determined by comparing the current pan value / tilt value acquired by the control unit 101 from the sub camera 400 with the new pan value / tilt value calculated in step S107 of FIG. 4(a). If the current pan value / tilt value is sufficiently close to the new pan value / tilt value, it can be determined that the tracking subject is present within the shooting angle of view of the sub camera 400. Alternatively, if the pan / tilt speed value calculated in step S108 is sufficiently small, it can be determined that the tracked subject is present within the shooting angle of view of the sub camera 400 because the current pan / tilt value is approaching the new pan / tilt value.

[0153] In step S118, the control unit 101 executes the function of the feature information determining unit 125 in FIG. 3, and advances the process to step S119.

[0154] The feature information determination unit 125 has a function of determining feature information of a subject being tracked by the sub camera 400, that is, feature information of the subject to be transmitted to the EB 200. The feature information determination unit 125 reads out feature information STAT[n] of the subject detected by the image recognition unit 121 from the overhead image of the overhead camera 300 from the volatile memory 102. The feature information determination unit 125 also reads out identification information SUBJECT_ID of the subject being tracked determined by the tracking target determination unit 123 from the volatile memory 102. Then, the feature information determination unit 125 determines feature information STAT[i] corresponding to the subject being tracked from the feature information STAT[n], and stores it in the volatile memory 102. i is an index indicating the subject being tracked.

[0155] In step S119, the control unit 101 transmits a tracking start command and feature information STAT[i] of the tracked subject to the EB 200 via the communication unit 105, and the process proceeds to step S120.

[0156] By the processing of steps S117 to S119, a tracking start command and feature information of the tracking subject can be transmitted to the EB200 only when there is a high possibility that the tracking subject is present within the shooting angle of view of the sub-camera 400. This makes it possible to reduce the amount of communication compared to the case where information is transmitted for each process of Fig. 4(a) and Fig. 9(a).

[0157] In step S120, control unit 101 receives the comparison result of the subject from EB 200 via communication unit 105. If control unit 101 receives match information from EB 200 indicating that the subjects match, the process proceeds to step S121, and if control unit 101 receives mismatch information indicating that the subjects do not match, the process ends.

[0158] In step S121, the control unit 101 executes the function of the tracking state determination unit 126 in FIG. 3, changes the tracking state information STATE to "Tracking by EB200", and ends the process.

[0159] Next, the control process of the EB 200 will be described with reference to FIGS.

[0160] FIG. 9B shows the control process of the EB 200, and shows the detailed process of step S203 in FIG.

[0161] In step S210, control unit 201 determines whether or not it has received from WS 100, via communication unit 205, a tracking start command and feature information STAT[i] of the tracking subject obtained from the overhead image of overhead camera 300. If control unit 201 has received the tracking start command and feature information STAT[i] of the tracking subject from WS 100, it proceeds to step S211;

[0162] In steps S211 to S214, the control unit 201 executes the function of the tracking target determination unit 222 in FIG. 3, and determines whether the feature information STAT[i] received from the WS 100 and the feature information STAT_SUB[m] obtained from the sub-image of the sub-camera 400 satisfy a predetermined condition.

[0163] The tracking target determination unit 222 has a function of calculating a similarity between the feature information STAT[i] received from the WS 100 and the feature information STAT_SUB[m] obtained from the sub-image of the sub-camera 400. The tracking target determination unit 222 also has a function of comparing the similarity of the feature information with a threshold value stored in the volatile memory 102, and storing the comparison result in the volatile memory 102. For example, when two people are present in the sub-image of the sub-camera 400, the tracking target determination unit 222 calculates a similarity between the feature information (STAT_SUB[1], STAT_SUB[2]) of the two people and the feature information STAT[i] received from the WS 100. The similarity is calculated as a cosine similarity between the feature information vectors, and a value between 1 and 0 is obtained as the similarity. The control unit 201 stores the similarities calculated for the m subjects in the volatile memory 202.

[0164] In step S211, the control unit 201 executes the function of the tracking target determination unit 222 in FIG. 3 to perform a comparison process of the feature information, and proceeds to step S212.

[0165] In step S212, control unit 201 determines whether or not a subject with highly similar feature information exists, based on the comparison result in step S211. The existence of a subject with highly similar feature information means that the same subject is photographed by overhead camera 300 and sub camera 400. If control unit 201 determines that a subject with highly similar feature information exists, control unit 201 proceeds to step S214, and if control unit 201 determines that a subject with highly similar feature information does not exist, control unit 201 proceeds to step S213.

[0166] The control unit 201 reads a predetermined threshold value from the volatile memory 202, and when the similarity is equal to or greater than the threshold value as a predetermined condition, or when a subject with a higher similarity exists, or when the subjects match, it determines that a subject with high similarity in feature information exists, and stores the identification information ID of the subject in the volatile memory 202. The control unit 201 also updates information MATCH indicating whether or not a subject with high similarity in feature information exists, and stores the information in the volatile memory 202. In this embodiment, if the value of MATCH is 0, there is no subject with high similarity in feature information, that is, the subjects do not match between the overhead camera 300 and the sub camera 400. If the value of MATCH is 1, there is a subject with high similarity in feature information, that is, the subjects match between the overhead camera 300 and the sub camera 400. If a subject with high similarity in feature information exists, the control unit 201 stores MATCH=1 in the volatile memory 202, and proceeds to step S214. If there is no subject with a high similarity in feature information, the control unit 201 stores MATCH=0 in the volatile memory 202, and the process proceeds to step S213.

[0167] Here, the similarity of feature information of the subject detected from the overhead image captured by the overhead camera 300 and the sub-image captured by the sub camera 400 will be described with reference to FIG.

[0168] Fig. 10(a) shows the positional relationship between the shooting position and shooting direction of the overhead camera 300 and the shooting position and shooting direction of the sub camera 400. Fig. 10(b) shows the subject detected from the overhead image of the overhead camera 300 and the tracked subject.

[0169] Assume that subjects A, B, and C are detected from the overhead image of overhead camera 300, and the subject being tracked by sub camera 400 is subject C. The feature information of the subject being tracked by sub camera 400 transmitted from sub camera 400 to WS 100 is information corresponding to subject C. Figures 10(c) and (e) show the sub-images of sub camera 400, and Figures 10(d) and (f) show the similarity between the feature information of the subject being tracked by sub camera 400 and the feature information of the subject detected from the sub-image.

[0170] As shown in Fig. 10(c), when the sub camera 400 is photographing subjects A and B, the similarity is calculated between the feature information of subject C in the overhead image of the overhead camera 300 and each feature information of subject A or subject B in the sub image of the sub camera 400. As shown in Fig. 10(d), the similarity is low between the feature information of subject C in the overhead image of the overhead camera 300 and the feature information of subject A or subject B in the sub image of the sub camera 400. In this case, for example, when the threshold value of the subject similarity is 0.7, the result is that both subjects A and B do not match.

[0171] Also, as shown in FIG. 10(e), when the sub camera 400 captures subjects B and C, the similarity between the feature information of subject C in the overhead image of the overhead camera 300 and the feature information of subject B or subject C in the sub image of the sub camera 400 is calculated. The subject C in the overhead image of the overhead camera 300 and the subject C in the sub image of the sub camera 400 have different forms in the images because the camera shooting positions and shooting directions are different. For example, when the subject C faces or faces the body toward the overhead camera 300, the subject C faces forward in the overhead image of the overhead camera 300 and is closer to sideways in the sub image of the sub camera 400. The inference model for identifying the subject in the image recognition unit 121 of the WS100 and the image recognition unit 221 of the EB200 is a model that learns images of the same subject captured from multiple different directions. Therefore, even if the same subject is photographed by multiple cameras with different photographing positions and directions and has a different form in each photographed image, the similarity of the feature information is high. That is, as shown in Fig. 10(f), the similarity of the feature information of subject C in the overhead image of overhead camera 300 and the feature information of subject C in the sub-image of sub camera 400 is high. As a result, for example, when the threshold value of the subject similarity is 0.7, subject B will be determined to be a mismatch and subject C will be determined to be a match, and subject C can be determined to be the same subject.

[0172] Returning to the explanation of FIG. 9B, in step S213, the control unit 201 reads MATCH=0 from the volatile memory 202, transmits it to the WS 100 via the communication unit 205, and ends the process.

[0173] In step S214, the control unit 201 reads out the identification information ID of the subject for which the highest similarity has been calculated from the volatile memory 102, stores it in the volatile memory 102 as the tracking subject SUBJECT_ID, and proceeds to step S215. By selecting the subject for which the highest similarity has been calculated, even if there are subjects wearing similar clothes, for example, it is possible to set the most likely subject among them as the tracking target.

[0174] In step S215, the control unit 201 reads MATCH=1 from the volatile memory 202, transmits it to the WS 100 via the communication unit 205, and ends the process.

[0175] FIG. 9C shows the control process of the EB 200, and shows the detailed process of step S204 in FIG.

[0176] In step S220, the control unit 201 determines whether or not a tracking stop command has been received from the WS 100 via the communication unit 205. If a tracking stop command has been received from the WS 100, the control unit 201 proceeds to step S221, and if not, the control unit 201 proceeds to step S223.

[0177] In step S221, the control unit 201 transmits a control command to stop the panning / tilting operation to the sub-camera 400 via the communication unit 205, and the process proceeds to step S222.

[0178] In step S222, the control unit 201 deletes the tracking subject SUBJECT_ID stored in the volatile memory 202, and the process proceeds to step S201.

[0179] In step S223, the control unit 201 determines whether or not a tracking continuation confirmation request has been received from the WS 100 via the communication unit 205. If a tracking continuation confirmation request has been received from the WS 100, the control unit 201 proceeds to step S224, and if not, the control unit 201 ends the process.

[0180] In step S224, the control unit 201 reads out the subject recognition result by the image recognition unit 221 from the volatile memory 202, and determines whether or not the tracking subject SUBJECT_ID is detected. If the control unit 201 determines that the tracking subject SUBJECT_ID is detected by the image recognition unit 221, the process proceeds to step S226, and if not, the process proceeds to step S225.

[0181] In step S225, the control unit 201 transmits "Continue tracking NG" to the WS 100 via the communication unit 205, and the process returns to step S201.

[0182] In step S226, the control unit 201 transmits "Continue tracking OK" to the WS 100 via the communication unit 205, and ends the process.

[0183] The above is the detailed control process of the EB200.

[0184] According to the above-described first embodiment, the same subject can be recognized by the multiple cameras 300 and 400 with different shooting positions and shooting directions. Therefore, a specific subject can be tracked by appropriately switching between the control of the sub-camera 400 by the WS 100 and the control of the sub-camera 400 by the EB 200.

[0185] When the subject to be tracked does not exist in the sub-image of the sub-camera 400, the WS 100 controls the sub-camera 400, and when the subject to be tracked exists in the shooting angle of view of the sub-camera 400, the control of the sub-camera 400 can be handed over from the WS 100 to the EB 200. Also, when the subject to be tracked moves at high speed and is lost, or when the subject to be tracked is changed, tracking can be continued by controlling the sub-camera 400 with the WS 100.

[0186] In the first embodiment, the WS100 and the EB200 switch whether or not to transmit the pan value / tilt value to the sub camera 400, but the present invention is not limited to this example. For example, the pan value / tilt value may be transmitted from the WS100 and the EB200 to the sub camera 400 regardless of the tracking state, and the sub camera 400 may control which device the pan value / tilt value received from to perform the pan operation / tilt operation. In this case, the process of the WS100 may omit the process of step S106 in FIG. 4(a), and before the process of step S107 in FIG. 4(a), the control unit 101 may add a process of transmitting tracking state information STATE to the sub camera 400. The process of the EB200 may omit the processes of steps S205 and S206 in FIG. 4(b) and step S221 in FIG. 9(c).

[0187] When the tracking state information STATE received from WS100 is "tracking by EB200", the sub-camera 400 controls to perform a panning operation / tilting operation in response to a control command received from EB200. When the tracking state information STATE received from WS100 is "tracking by WS100", the sub-camera 400 controls to perform a panning operation / tilting operation in response to a control command received from WS100.

[0188] The edge box (EB) 200 may be integrated with the sub-camera 400, or the function of the EB 200 may be built into the sub-camera 400.

[0189] [Embodiment 2] In the first embodiment, an example has been described in which either the WS 100 or the EB 200 controls the sub-camera 400. In the second embodiment, an example will be described in which the EB 200 is omitted and the WS 100 controls the sub-camera 400 based on the overhead image of the overhead camera 300 and the sub-image of the sub-camera 400.

[0190] In the second embodiment, the sub camera 400 is controlled using either the pan value / tilt value calculated based on the overhead image of the overhead camera 300 or the pan value / tilt value calculated based on the sub image of the sub camera 400.

[0191] 1 without the EB 200, and differs from the first embodiment in that a sub-image from the sub-camera 400 is input to the WS 100. Operations other than those of the WS 100 are the same as those of the first embodiment.

[0192] In basic operation, the overhead camera 300 transmits an overhead image to the WS 100. The sub-camera 400 transmits a sub-image to the WS 100. The sub-camera 400 also has a PTZ function.

[0193] The WS100 detects a subject from the overhead image of the overhead camera 300 and the sub-image of the sub-camera 400, and changes the imaging direction of the sub-camera 400 to the direction of the tracked subject based on the subject recognition result. Until the shooting direction of the sub-camera 400 becomes the direction of the tracked subject, the WS100 controls the sub-camera 400 based on the subject recognition result of the overhead image of the overhead camera 300. After the shooting direction of the sub-camera 400 becomes the direction of the tracked subject, the WS100 calculates feature information of the tracked subject from the overhead image of the overhead camera 300, and calculates feature information of the subject from the sub-image of the sub-camera 400. Then, the WS100 controls the sub-camera 400 based on these feature information. The feature information is information that can identify that the same subject is the same when the same subject is shot by multiple cameras with different shooting positions and / or shooting directions.

[0194] According to the second embodiment, the sub camera 400 can be controlled based on the subject recognition result of either the overhead image of the overhead camera 300 or the sub image of the sub camera 400, to track the tracking subject.

[0195] The hardware configurations of the WS 100, the overhead camera 300, and the sub-camera 400 are the same as those in FIG. 2 of the first embodiment.

[0196] First, the functional configuration of the WS 100 for implementing the control process of this embodiment will be described with reference to FIG.

[0197] The functions of the WS 100 are realized by hardware and / or software. If the functional units shown in Fig. 11 are configured by hardware instead of by software, it is sufficient to have a circuit configuration corresponding to each functional unit in Fig. 11.

[0198] WS100 includes an image recognition unit 121, an object of interest determination unit 122, a tracking target determination unit 123, a control information generation unit 124, a feature information determination unit 125, a tracking state determination unit 126, an image recognition unit 127, and a tracking target determination unit 128. Software for realizing these functions is stored in non-volatile memory 103, and the control unit 101 loads it into volatile memory 102 and executes it.

[0199] The functions of the image recognition unit 121, the target subject determination unit 122, the tracking target determination unit 123, and the feature information determination unit 125 are similar to those in FIG. 3 of the first embodiment.

[0200] The functions and basic operations of the WS 100 will be described with reference to FIGS.

[0201] The processes from step S501 to step S504 are similar to those from step S101 to S104 in FIG. 4(a) of the first embodiment.

[0202] In step S505, the control unit 101 transmits a shooting command to the sub-camera 400 via the communication unit 105, receives the captured sub-image from the sub-camera 400, stores it in the volatile memory 102, and proceeds to step S506.

[0203] In step S506, the control unit 101 executes the function of the image recognition unit 127 in FIG. 11, and the process proceeds to step S507.

[0204] The functions of the image recognition unit 127 can be achieved by replacing the control unit 201 with the control unit 101, the volatile memory 202 with the volatile memory 102, and the non-volatile memory 203 with the non-volatile memory 103 in the description of the image recognition unit 221 of the EB 200 of the first embodiment.

[0205] 11, compares the feature information calculated in steps S502 and S506, and updates the tracking state information STATE. Furthermore, the control unit 101 stores the tracking subject SELECT_ID and the tracking state information STATE in the volatile memory 102, and the process proceeds to step S508.

[0206] The tracking state information STATE includes information on either "tracking using overhead image" or "tracking using sub-image." "Tracking using overhead image" indicates a state in which the tracking subject is tracked by controlling sub-camera 400 based on the subject recognition result of the overhead image of overhead camera 300. "Tracking using sub-image" indicates a state in which the tracking subject is tracked by controlling sub-camera 400 based on the subject recognition result of the sub-image of sub-camera 400. The process of step S507 will be described in detail later.

[0207] The processes in steps S508 to S510 are executed by the function of the control information generating unit 124 in FIG.

[0208] In step S508, the control unit 101 reads the tracking state information STATE from the volatile memory 102, and determines whether "tracking using an overhead image" or "tracking using a sub-image" based on the tracking state information STATE. If the control unit 101 determines that "tracking using an overhead image" is in progress, the process proceeds to step S510, and if the control unit 101 determines that "tracking using a sub-image is in progress", the process proceeds to step S509.

[0209] In step S509, the control unit 101 calculates the pan value / tilt value of the sub camera 400 based on the subject recognition result of the sub image of the sub camera 400, and proceeds to step S511. The process of step S509 can be performed by replacing the control unit 201 with the control unit 101 and the volatile memory 202 with the volatile memory 102 in the process of the control information generation unit 223 in FIG.

[0210] In step S510, the control unit 101 calculates the pan value / tilt value of the sub camera 400 based on the subject recognition result of the overhead image of the overhead camera 300, and proceeds to step S511. The process of step S510 can be performed by replacing the control unit 201 with the control unit 101 and the volatile memory 202 with the volatile memory 102 in the process of the control information generation unit 223 in FIG.

[0211] In step S511, the control unit 101 executes the function of the control information generating unit 124 in FIG. 3, and advances the process to step S512.

[0212] The processes in steps S511 and S512 are similar to those in steps S108 and S109 in FIG.

[0213] The above is the basic operation of the WS100.

[0214] Next, the control process of the WS 100 will be described with reference to FIG.

[0215] FIG. 13 shows the control process of the WS 100, and shows the detailed process of step S507 in FIG.

[0216] The process of step S520 is similar to that of step S110 in FIG.

[0217] In step S521, the control unit 101 executes the function of the tracking state determination unit 126 in FIG. 11, and changes the tracking state information STATE to "tracking using an image from an overhead camera".

[0218] The tracking state determination unit 126 has a function of updating the tracking state information STATE stored in the volatile memory 102 .

[0219] In step S522, the control unit 101 reads the tracking state information STATE from the volatile memory 102, and determines whether "tracking using an overhead image" or "tracking using a sub-image" based on the tracking state information STATE. If the control unit 101 determines that "tracking using an overhead image" is in progress, the process proceeds to step S525, and if the control unit 101 determines that "tracking using a sub-image is in progress", the process proceeds to step S523.

[0220] The process of step S523 can be achieved by replacing the control unit 201 with the control unit 101 and the volatile memory 202 with the volatile memory 102 in the process of step S224 in FIG. 9B.

[0221] In step S524, the control unit 101 executes the function of the tracking state determination unit 126 in FIG. 11 to change the tracking state information STATE to "tracking using overhead image".

[0222] The processes in steps S525 and S526 are similar to those in steps S117 and S118 in FIG.

[0223] The process of steps S527 to S529 can be achieved by replacing the control unit 201 with the control unit 101 and the volatile memory 202 with the volatile memory 102 in the process of steps S211 to S214 in FIG. 9B.

[0224] In step S530, the control unit 101 executes the function of the tracking state determination unit 126 in FIG. 11 to change the tracking state information STATE to "tracking using sub-image", and ends the process.

[0225] According to the above-mentioned second embodiment, the WS 100 switches whether to control the sub-camera 400 based on the subject recognition result of the overhead image of the overhead camera 300 or the sub-image of the sub-camera 400. This makes the EB 200 of the first embodiment unnecessary, and the same effect as the first embodiment can be obtained with a simplified system configuration.

[0226] [Embodiment 3] In the first and second embodiments, an example of a system including the overhead camera 300 and the sub-camera 400 has been described.

[0227] In the third embodiment, an example of a system including a main camera 500 in addition to an overhead camera 300 and a sub-camera 400 will be described.

[0228] FIG. 14 is a system configuration diagram of the third embodiment.

[0229] The third embodiment differs from the first embodiment in that a main camera 500 is provided, and a subject to be tracked by the sub camera 400 is determined based on a main image captured by the main camera 500. The following description will focus on the differences from the first embodiment.

[0230] In the third embodiment, the main camera 500 has a PTZ function. The target subject determination unit 122 of the WS 100 determines (estimates) a target subject of the main camera 500 from the shooting range of the main camera 500, and determines a tracking subject of the sub camera 400 based on the target subject of the main camera 500. The tracking subject of the sub camera 400 may be the same subject as the target subject of the main camera 500, or may be a different subject.

[0231] Next, an example of determining a tracking subject of the sub camera 400 based on a role (ROLE) set to the sub camera 400 will be described.

[0232] The role of the sub camera 400 indicates the subject of interest in the main camera 500, the subject to be tracked by the sub camera 400 associated with the zoom operation, and the control content of the zoom operation. The role of the sub camera 400 can be set by the user via an operation unit provided in the WS100 or EB200. In addition, when multiple sub cameras are installed, any of the multiple sub cameras can be set as the main camera, and the setting of the main camera may be set by the user via an operation unit provided in the WS100 or EB200. The role of the sub camera 400 and the setting method of the main camera are not limited to the above method, and any method may be used.

[0233] FIG. 15 shows an example of the roles and contents that can be set for the sub-camera 400.

[0234] When the role (ROLE) is "main follow", the role (CAMERA_ROLE) of the sub camera 400 is to track the same subject as the subject that the main camera 500 is focusing on, and to perform zoom control in the same phase as the zoom operation of the main camera 500. Based on this role (CAMERA_ROLE), the zoom control value of the sub camera 400 is calculated. Here, the same phase in the zoom operation means that the zoom operations of the main camera 500 and the sub camera 400 are controlled in the same direction. For example, when the zoom control value of the main camera 500 is changed from the wide-angle side to the telephoto side, the zoom of the sub camera 400 is also changed from the wide-angle side to the telephoto side.

[0235] When the role (ROLE) is "main counter", the role (CAMERA_ROLE) of the sub camera 400 is to track the same subject as the subject that the main camera 500 is focusing on, and to perform zoom control in the opposite phase to the zoom operation of the main camera 500. The PTZ value of the sub camera 400 is calculated based on this role (CAMERA_ROLE). Here, the opposite phase in the zoom operation means that the zoom operations of the main camera 500 and the sub camera 400 are controlled in the opposite directions. For example, when the zoom control value of the main camera 500 is changed from the wide-angle side to the telephoto side, the zoom of the sub camera 400 is changed from the telephoto side to the wide-angle side.

[0236] When the role (ROLE) is "assist follow", the sub camera 400 tracks a subject other than the subject that the main camera 500 is focusing on, and performs zoom control in the same phase as the zoom operation of the main camera 500. Based on this role (CAMERA_ROLE), the zoom control value of the sub camera 400 is calculated.

[0237] When the role (ROLE) is "assist counter", the sub camera 400 tracks a subject other than the subject that the main camera 500 is focusing on, and performs zoom control in the opposite phase to the zoom operation of the main camera 500. Based on this role (CAMERA_ROLE), the zoom control value of the sub camera 400 is calculated. In the example of FIG. 15, "separate from main (left side)" is exemplified as the control content of the tracking subject for "assist follow" and "assist counter", but there may be "assist follow" and "assist counter" in which the tracking subject is "separate from main (right side)".

[0238] In addition, when the tracking subject is "separate from the main subject", it may also serve the role of tracking a subject in a position other than left and right (up and down, or front and back).

[0239] When there are multiple sub-cameras, a role may be set for each sub-camera.

[0240] Furthermore, in the third embodiment, an example has been described in which the control contents for the tracking subject and zoom are set as roles, but the control contents for only the tracking subject may be set as a role, or other items may be added.

[0241] In the third embodiment, a tracking subject of the sub camera 400 is set based on the main image of the main camera 500, and an example is described in which the first embodiment is combined with the third embodiment. However, the second embodiment may be combined with the third embodiment.

[0242] Furthermore, in a configuration including overhead camera 300 and sub-camera 400 as in the first and second embodiments, sub-camera 400 may be controlled to track a tracking subject based on both the overhead image and the sub-image captured by each camera.

[0243] In addition, in a configuration having a main camera 500 in addition to the overhead camera 300 and sub-camera 400 as in embodiment 3, the sub-camera 400 may be controlled to track the tracking subject based on any two or all of the overhead image, main image, and sub-image captured by each camera.

[0244] [Other embodiments] The present invention can also be realized by a process in which a program for implementing one or more of the functions of the above-described embodiments is supplied to a system or device via a network or a storage medium, and one or more processors in a computer of the system or device read and execute the program. The present invention can also be realized by a circuit (e.g., ASIC) that implements one or more of the functions.

[0245] The invention is not limited to the above-described embodiments, and various modifications and variations are possible without departing from the spirit and scope of the invention. Accordingly, the following claims are appended to apprise the public of the scope of the invention.

[0246] The disclosure of this specification includes the following system, control device, control method, and program. [Configuration 1] A system including a first imaging device and a second imaging device having different shooting directions, and a first control device and a second control device that control the second imaging device so as to track a predetermined subject based on a first image captured by the first imaging device or a second image captured by the second imaging device, The first control device includes: a first generating means for generating first feature information of the predetermined object included in the first image; a first control means for controlling the second imaging device so as to track the predetermined subject based on the first feature information, The second control device includes: a second generating means for generating second feature information of a subject included in the second image; a comparison means for comparing the first characteristic information generated by the first control device with the second characteristic information generated by the second generation means; and a second control means for controlling the second imaging device so as to track the predetermined subject based on the second feature information, the first feature information and the second feature information are information that can identify an identical subject when the same subject is photographed by a plurality of image capturing devices having different photographing directions, A system characterized by switching between a first state in which the first control device controls the second imaging device to track the specified subject based on the first feature information, and a second state in which the second control device controls the second imaging device to track the specified subject based on the second feature information, based on a result of the comparison by the comparison means. [Configuration 2] The first control device transmits the first characteristic information to the second control device; the first control means switches to the second state when the first characteristic information and the second characteristic information satisfy a predetermined condition based on a result of the comparison by the comparison means; The system according to configuration 1, characterized in that if the first characteristic information and the second characteristic information do not satisfy the predetermined condition, the system switches to the first state. [Configuration 3] the predetermined condition is that a similarity between the first feature information and the second feature information is equal to or greater than a threshold value; The system according to configuration 2, wherein the comparison means calculates a similarity between the first feature information and the second feature information, and outputs a result of comparing the similarity with the threshold value. [Configuration 4] the second control means controls the second imaging device to track the predetermined object when the predetermined object is present within a shooting range of the second imaging device; When the predetermined object is no longer present within a shooting range of the second imaging device, notify the first control device that tracking of the predetermined object cannot be continued; 4. The system according to any one of configurations 1 to 3, wherein the first control means receives the notification and switches from the second state to the first state. [Configuration 5] 5. The system according to any one of configurations 1 to 4, characterized in that, when the specified subject is changed, the first control means switches from the second state to the first state. [Configuration 6] The system described in configuration 5, wherein when the specified subject is changed, the first control means switches from the first state to the second state if the first feature information and the second feature information satisfy a specified condition. [Configuration 7] The first control device includes: a first tracking target determination means for determining the predetermined subject from subjects detected in the first image; a feature information determining means for determining the first feature information of the predetermined object and transmitting the first feature information to the second control device; a first control information generating means for generating first control information for controlling the photographing direction of the second control device so as to track the predetermined subject; The second control device includes: a second tracking target determination means for determining a predetermined subject from among the subjects detected from the second image based on the second feature information of the subject detected from the second image and the first feature information of the predetermined subject received from the first control device; and a second control information generating means for generating second control information for controlling a shooting direction of the second control device so as to track the specified subject. [Configuration 8] The system described in configuration 7, wherein the second imaging device controls the shooting direction of the second control device so as to track the specified subject based on control information acquired from the first control device or the second control device. [Configuration 9] The system described in configuration 7, wherein the second imaging device controls the shooting direction of the second control device so as to track the specified subject based on either control information acquired from the first control device or the second control device. [Configuration 10] 10. The system according to any one of configurations 7 to 9, wherein the control information includes at least one of a pan value and a tilt value. [Configuration 11] The first generation means generates the first feature information by performing an inference process using a trained model with the first image as an input; The system according to any one of configurations 1 to 10, wherein the second generation means generates the second feature information by performing inference processing using a trained model with the second image as an input. [Configuration 12] The trained model includes a first model for object detection and a second model for object identification; the first generating means generates first information indicating a position of a subject included in the first image by performing an inference process using the first model with the first image as an input; generating feature information of a subject included in the first image by performing an inference process using the second model with the first image and the first information as input; the second generating means generates second information indicating a position of a subject included in the second image by performing an inference process using the first model with the second image as an input; The system described in configuration 11, characterized in that it generates feature information of the subject contained in the second image by performing inference processing using the second model with the second image and the second information as input. [Configuration 13] The system described in configuration 12, wherein the second model for identifying a subject is a trained model that has been trained using images of a plurality of subjects taken from a plurality of different shooting directions as training data so as to increase the similarity of feature information for images of the same subject. [Configuration 14] A control device that controls a second imaging device to track a predetermined subject based on a first image captured by a first imaging device or a second image captured by a second imaging device having a shooting direction different from that of the first imaging device, A generating means for generating first feature information of the predetermined object included in the first image; a control unit for controlling the second imaging device so as to track the predetermined subject; the control means, based on a result of comparing second feature information of a subject included in the second image with the first feature information, switches between a first state in which the control device controls the second imaging device to track the predetermined subject based on the first feature information and a second state in which the external device controls the second imaging device to track the predetermined subject based on the second feature information; A control device characterized in that the first feature information and the second feature information are information that can identify that the same subject is photographed by multiple imaging devices with different shooting directions. [Configuration 15] A control device that controls a second imaging device so as to track a predetermined subject based on a second image captured by the second imaging device having a different imaging direction from that of the first imaging device, A generating means for generating second feature information of a subject included in the second image; a comparison means for comparing first feature information of the predetermined subject included in a first image captured by the first imaging device, the first feature information being acquired from an external device, with the second feature information; a control unit that controls the second imaging device so as to track the predetermined subject based on the second feature information, the first feature information and the second feature information are information that can identify an identical subject when the same subject is photographed by a plurality of image capturing devices having different photographing directions, the control means controls the second imaging device to track the specified subject based on the second feature information when the first feature information and the second feature information satisfy a specified condition based on a result of the comparison by the comparison means. [Configuration 16] A control device that controls a second imaging device to track a predetermined subject based on a first image captured by a first imaging device or a second image captured by a second imaging device having a shooting direction different from that of the first imaging device, a first generating means for generating first feature information of the predetermined object included in the first image; a second generating means for generating second feature information of a subject included in the second image; a control unit for controlling the second imaging device so as to track the predetermined subject; the first feature information and the second feature information are information that can identify an identical subject when the same subject is photographed by a plurality of image capturing devices having different photographing directions, the control means switches between a first state in which the second imaging device is controlled to track the specified subject based on the first feature information and a second state in which the second imaging device is controlled to track the specified subject based on the second feature information, based on a result of comparing the first feature information with the second feature information. [Configuration 17] A control method for a control device that controls a second imaging device to track a predetermined subject based on a first image captured by a first imaging device or a second image captured by a second imaging device having a shooting direction different from that of the first imaging device, comprising: A generating step of generating first feature information of the predetermined object included in the first image; and a control step of controlling the second imaging device so as to track the predetermined subject, In the control step, based on a result of comparing second feature information of a subject included in the second image with the first feature information, the external device switches between a first state in which the control device controls the second imaging device to track the predetermined subject based on the first feature information and a second state in which the external device controls the second imaging device to track the predetermined subject based on the second feature information; A method characterized in that the first feature information and the second feature information are information that can identify the same subject when the same subject is photographed by multiple imaging devices with different shooting directions. [Configuration 18] A control method for a control device that controls a second imaging device so as to track a predetermined subject based on a second image captured by the second imaging device having a shooting direction different from that of the first imaging device, A generating step of generating second feature information of a subject included in the second image; a comparison step of comparing first feature information of a predetermined subject included in a first image captured by the first imaging device, the first feature information being acquired from an external device, with the second feature information; and a control step of controlling the second imaging device so as to track the predetermined subject based on the second feature information, the first feature information and the second feature information are information that can identify an identical subject when the same subject is photographed by a plurality of image capturing devices having different photographing directions, The method characterized in that in the control step, if the first feature information and the second feature information satisfy a predetermined condition based on the result of the comparison, the second imaging device is controlled to track the specified subject based on the second feature information. [Configuration 19] A control method for a control device that controls a second imaging device to track a predetermined subject based on a first image captured by a first imaging device or a second image captured by a second imaging device having a shooting direction different from that of the first imaging device, comprising: a first generation step of generating first feature information of the predetermined object included in the first image; a second generation step of generating second feature information of a subject included in the second image; and a control step of controlling the second imaging device so as to track the predetermined subject, the first feature information and the second feature information are information that can identify an identical subject when the same subject is photographed by a plurality of image capturing devices having different photographing directions, The method, characterized in that in the control step, based on a result of comparing the first feature information with the second feature information, switching between a first state in which the second imaging device is controlled to track the specified subject based on the first feature information and a second state in which the second imaging device is controlled to track the specified subject based on the second feature information. [Configuration 20] A program for causing a computer to function as the control device according to any one of configurations 14 to 16. [Explanation of symbols]

[0247] 100...first control device (workstation / WS), 200...second control device (edge ​​box / EB), 300...first imaging device (overhead camera), 400...second imaging device (sub-camera), 101, 201, 301, 401...control unit

Claims

1. A system including a first imaging device and a second imaging device having different shooting directions, and a first control device and a second control device that control the second imaging device so as to track a predetermined subject based on a first image captured by the first imaging device or a second image captured by the second imaging device, The first control device includes: a first generating means for generating first feature information of the predetermined subject included in the first image; a first control unit that controls the second imaging device so as to track the predetermined subject based on the first feature information, The second control device includes: a second generating means for generating second feature information of a subject included in the second image; a comparison means for comparing the first characteristic information generated by the first control device with the second characteristic information generated by the second generation means; and a second control means for controlling the second imaging device so as to track the predetermined subject based on the second feature information, the first feature information and the second feature information are information that can identify an identical subject when the same subject is photographed by a plurality of image capturing devices having different photographing directions, A system characterized by switching between a first state in which the first control device controls the second imaging device to track the specified subject based on the first feature information, and a second state in which the second control device controls the second imaging device to track the specified subject based on the second feature information, based on a result of the comparison by the comparison means.

2. The first control device transmits the first characteristic information to the second control device; the first control means switches to the second state when the first characteristic information and the second characteristic information satisfy a predetermined condition based on a result of the comparison by the comparison means; The system according to claim 1 , wherein the system switches to the first state if the first characteristic information and the second characteristic information do not satisfy the predetermined condition.

3. the predetermined condition is that a similarity between the first feature information and the second feature information is equal to or greater than a threshold value; 3. The system according to claim 2, wherein the comparison means calculates a similarity between the first feature information and the second feature information, and outputs a result of comparing the similarity with the threshold value.

4. the second control means controls the second imaging device to track the predetermined object when the predetermined object is present within a shooting range of the second imaging device; When the predetermined object is no longer present within a shooting range of the second imaging device, notify the first control device that tracking of the predetermined object cannot be continued; 2. The system according to claim 1, wherein the first control means receives the notification and switches from the second state to the first state.

5. 2. The system of claim 1, wherein said first control means switches from said second state to said first state when said predetermined subject is changed.

6. The system described in claim 5, wherein when the specified subject is changed, the first control means switches from the first state to the second state if the first feature information and the second feature information satisfy a specified condition.

7. The first control device includes: a first tracking target determination means for determining the predetermined subject from subjects detected in the first image; a feature information determining means for determining the first feature information of the predetermined subject and transmitting the first feature information to the second control device; a first control information generating means for generating first control information for controlling an imaging direction of the second control device so as to track the predetermined subject; The second control device includes: a second tracking target determination means for determining a predetermined subject from among the subjects detected from the second image based on the second feature information of the subject detected from the second image and the first feature information of the predetermined subject received from the first control device; The system according to claim 1, further comprising: second control information generating means for generating second control information for controlling the shooting direction of the second control device so as to track the specified subject.

8. The system described in claim 7, characterized in that the second imaging device controls the shooting direction of the second control device so as to track the specified subject based on control information acquired from the first control device or the second control device.

9. The system described in claim 7, characterized in that the second imaging device controls the shooting direction of the second control device so as to track the specified subject based on either control information acquired from the first control device or the second control device.

10. 8. The system of claim 7, wherein the control information includes at least one of a pan value and a tilt value.

11. The first generating means generates the first feature information by performing an inference process using a trained model with the first image as an input; The system according to claim 1, characterized in that the second generation means generates the second feature information by performing inference processing using a trained model with the second image as input.

12. The trained model includes a first model for object detection and a second model for object identification, the first generating means generates first information indicating a position of a subject included in the first image by performing an inference process using the first model with the first image as an input; performing an inference process using the second model with the first image and the first information as inputs to generate feature information of a subject included in the first image; the second generating means generates second information indicating a position of a subject included in the second image by performing an inference process using the first model with the second image as an input; The system described in claim 11, characterized in that the second image and the second information are used as inputs to perform inference processing using the second model, thereby generating feature information of the subject contained in the second image.

13. The system described in claim 12, characterized in that the second model for subject identification is a trained model that has been trained using images of multiple subjects taken from multiple different shooting directions as learning data, so as to increase the similarity of feature information for images of the same subject.

14. A control device that controls a second imaging device to track a predetermined subject based on a first image captured by a first imaging device or a second image captured by a second imaging device having a shooting direction different from that of the first imaging device, A generating means for generating first feature information of the predetermined object included in the first image; a control unit for controlling the second imaging device so as to track the predetermined subject; the control means, based on a result of comparing second feature information of a subject included in the second image with the first feature information, switches between a first state in which the control device controls the second imaging device to track the predetermined subject based on the first feature information and a second state in which the external device controls the second imaging device to track the predetermined subject based on the second feature information; A control device characterized in that the first feature information and the second feature information are information that can identify that the same subject is photographed by multiple imaging devices with different shooting directions.

15. A control device that controls a second imaging device so as to track a predetermined subject based on a second image captured by the second imaging device having a shooting direction different from that of the first imaging device, A generating means for generating second feature information of a subject included in the second image; a comparison means for comparing first feature information of the predetermined subject included in a first image captured by the first imaging device, the first feature information being acquired from an external device, with the second feature information; a control unit that controls the second imaging device so as to track the predetermined subject based on the second feature information, the first feature information and the second feature information are information that can identify an identical subject when the same subject is photographed by a plurality of image capturing devices having different photographing directions, the control means controls the second imaging device to track the specified subject based on the second feature information when the first feature information and the second feature information satisfy a specified condition based on a result of the comparison by the comparison means.

16. A control device that controls a second imaging device to track a predetermined subject based on a first image captured by a first imaging device or a second image captured by a second imaging device having a shooting direction different from that of the first imaging device, a first generating means for generating first feature information of the predetermined subject included in the first image; a second generating means for generating second feature information of a subject included in the second image; a control unit for controlling the second imaging device so as to track the predetermined subject; the first feature information and the second feature information are information that can identify an identical subject when the same subject is photographed by a plurality of image capturing devices having different photographing directions, the control means switches between a first state in which the second imaging device is controlled to track the specified subject based on the first feature information and a second state in which the second imaging device is controlled to track the specified subject based on the second feature information based on a result of comparing the first feature information with the second feature information.

17. A control method for a control device that controls a second imaging device to track a predetermined subject based on a first image captured by a first imaging device or a second image captured by a second imaging device having a shooting direction different from that of the first imaging device, comprising: A generating step of generating first feature information of the predetermined object included in the first image; a control step of controlling the second imaging device so as to track the predetermined subject, In the control step, based on a result of comparing second feature information of a subject included in the second image with the first feature information, the external device switches between a first state in which the control device controls the second imaging device to track the predetermined subject based on the first feature information and a second state in which the external device controls the second imaging device to track the predetermined subject based on the second feature information; A method characterized in that the first feature information and the second feature information are information that can identify an identical subject when the same subject is photographed by multiple imaging devices with different shooting directions.

18. A control method for a control device that controls a second imaging device so as to track a predetermined subject based on a second image captured by the second imaging device having an imaging direction different from that of the first imaging device, A generating step of generating second feature information of a subject included in the second image; a comparison step of comparing first feature information of a predetermined subject included in a first image captured by the first imaging device, the first feature information being acquired from an external device, with the second feature information; a control step of controlling the second imaging device so as to track the predetermined subject based on the second feature information, the first feature information and the second feature information are information that can identify an identical subject when the same subject is photographed by a plurality of image capturing devices having different photographing directions, The method characterized in that in the control step, based on the result of the comparison, if the first feature information and the second feature information satisfy a predetermined condition, the second imaging device is controlled to track the specified subject based on the second feature information.

19. A control method for a control device that controls a second imaging device to track a predetermined subject based on a first image captured by a first imaging device or a second image captured by a second imaging device having a shooting direction different from that of the first imaging device, comprising: a first generation step of generating first feature information of the predetermined object included in the first image; a second generation step of generating second feature information of a subject included in the second image; a control step of controlling the second imaging device so as to track the predetermined subject, the first feature information and the second feature information are information that can identify an identical subject when the same subject is photographed by a plurality of image capturing devices having different photographing directions, The method characterized in that the control step switches between a first state in which the second imaging device is controlled to track the specified subject based on the first feature information and a second state in which the second imaging device is controlled to track the specified subject based on the second feature information based on a result of comparing the first feature information and the second feature information.

20. A program for causing a computer to function as the control device according to any one of claims 14 to 16.

Citation Information

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