Information processing device, information processing method, and information processing program

Abstract

To improve the detection accuracy of an object.SOLUTION: An information processing device 100 of the present invention comprises: a change unit 122 which changes the number of images per unit time used to detect an object included in an image captured by an imaging device 200 according to an angle of view of the imaging device 200; and a detection unit 123 which detects the object using each image of the number of images per changed unit time among the images captured by the imaging device 200.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] 2. Description of the Related Art Conventionally, various techniques relating to security cameras and surveillance cameras have been proposed, such as techniques relating to store-installed security camera devices, and techniques relating to surveillance camera devices and programs used in surveillance camera devices. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2014-041570 A Summary of the Invention [Problem to be solved by the invention]

[0004] In conventional technology, for example, if the angle of view of the imaging device is small, there are cases where an object passing within the angle of view cannot be detected, resulting in reduced accuracy in detecting an object.

[0005] The present invention has been made in view of the above, and has an object to provide an information processing device, an information processing method, and an information processing program that can improve the accuracy of object detection. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the objective, the information processing device is characterized in having a modification unit that changes the number of images per unit time used to detect an object contained in an image captured by the imaging device in accordance with the angle of view of the imaging device, and a detection unit that performs detection of the object using each of the images captured by the imaging device with the modified number of images per unit time. Effect of the Invention

[0007] According to the present invention, it is possible to improve the object detection accuracy. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram showing an example of a configuration of an information processing system according to an embodiment. [Diagram 2] FIG. 2 is a diagram for explaining the problem of the reference technology. [Diagram 3] FIG. 3 is a block diagram illustrating an example of the configuration of the information processing device according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of the estimation process of the information processing device according to the embodiment. [Diagram 5] FIG. 5 is a diagram illustrating an example of the estimation process of the information processing device according to the embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of a change process of the information processing device according to the embodiment. [Figure 7] FIG. 7 is a diagram illustrating an example of a change process of the information processing device according to the embodiment. [Figure 8] FIG. 8 is a diagram illustrating an example of a change process of the information processing device according to the embodiment. [Figure 9] FIG. 9 is a flowchart showing an example of a process flow of the information processing device according to the embodiment. [Figure 10] FIG. 10 is a diagram illustrating an example of a computer that executes an information processing program. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, with reference to the drawings, an embodiment of an information processing device, an information processing program, and an information processing method according to the present application will be described in detail. Note that the present invention is not limited to the embodiment. In addition, in the description of the drawings, the same parts are denoted by the same reference numerals, and duplicated explanations will be omitted.

[0010] [Information processing system configuration] First, the configuration of the information processing system 1 will be described with reference to FIG. 1. FIG. 1 is a diagram showing an example of the configuration of the information processing system 1 according to the embodiment. As shown in FIG. 1, the information processing system 1 has an information processing device 100 and an imaging device 200. The information processing device 100 and the imaging device 200 are connected by wire or wirelessly. Note that, although FIG. 1 shows one information processing device 100 and three imaging devices 200, the number of information processing devices 100 and imaging devices 200 is not limited in the information processing system 1. That is, the information processing system 1 is composed of any number of information processing devices 100 and any number of imaging devices 200. Each of these devices will be described below.

[0011] The imaging device 200 is an example of a security camera or a monitoring camera, and is a camera that captures images. The imaging device 200 captures images with a set resolution, format, frame rate, etc. The images include still images and videos.

[0012] The information processing device 100 is an example of a computer that analyzes an image captured by the imaging device 200 and detects an object in the image. For example, the information processing device 100 determines whether or not a detection target object is included in each of the images captured per unit time by the imaging device 200. Here, the number of images per unit time means a detection frame rate when detecting an object.

[0013] The detection frame rate is a frame rate used by the information processing device 100 to detect an object, and is different from the frame rate of a moving image. That is, the imaging device 200 captures a moving image at a set frame rate and outputs the captured moving image to the information processing device 100, and the information processing device 100 detects an object from the moving image acquired from the imaging device 200 at the set detection frame rate.

[0014] For example, when 40 fps (frames per second) is set as the frame rate of the moving image and 5 fps is set as the detection frame rate, the imaging device 200 captures the moving image at the speed of 40 fps set as the frame rate, and transmits the moving image consisting of 40 images per second to the information processing device 100. Then, since 5 fps is set as the detection frame rate, the information processing device 100 detects an object by determining whether an object is included in each image using 5 images per second for the moving image consisting of 40 images per second.

[0015] In this specification, the angle of view refers not only to the range that the imaging device 200 can capture, but also to the range in which an object can be detected within the range that the imaging device 200 can capture. Moreover, the object includes not only moving objects such as people, animals, plants, and machines, but also any object to be detected, such as non-moving objects such as shelves, carts, and products.

[0016] [Reference technology issues] A known reference technology for performing such object detection is a technology that determines whether each image of a number of images per unit time contains a detection target object, and detects the object if it is determined that the object is contained a threshold number of times or more. However, with this reference technology, the angle of view of the imaging device is small, and therefore the accuracy of object detection may be reduced, such as in the case where an object passing within the angle of view cannot be detected.

[0017] Here, the problem of the above-mentioned reference technology will be described. Fig. 2 is a diagram for explaining the problem of the reference technology. In the reference technology, an image captured by an imaging device such as a camera is transmitted to an external system such as an AI application, and various processes such as detecting an object included in the image are performed in the external system.

[0018] In such a reference technology, an external system such as an AI application detects an object when the object is included in an image per unit time more than the threshold number of times. For example, under the condition that the detection frame rate of the imaging device is 10 fps, the threshold number is 4, and a person to be detected is detected when the person to be detected is captured in 4 frames, if the angle of view is large, the person can be detected because the person is captured in 5 frames before passing through the angle of view, as shown in Figure 2 (1).

[0019] On the other hand, even if the detection frame rate of the imaging device is 10 fps as in Fig. 2(1), if the angle of view is small, the person cannot be detected because the person passes through the angle of view before being captured in four frames, as shown in Fig. 2(2). In other words, even in a situation where a person must be detected, the object detection processing speed (detection frame rate to be processed) is slow, and so objects may not be detected.

[0020] Problems with detection accuracy due to the angle of view of the imaging device arise not only from the angle at which the image is captured by the imaging device, but also from the environment the imaging device is installed in. For example, even with a wide-angle camera, there may be cases where the range in which the target object can actually be detected is smaller than that of a narrow-angle camera, such as when there is an obstacle in front of the installed camera, when a wall surface is continuously captured, or when there is an area where the target object cannot pass through.

[0021] Furthermore, in the reference technology, resources may not be used effectively. For example, an unnecessarily high detection frame rate may be set even though the angle of view of the imaging device is large. For example, in the case of a wide-angle camera, a frame rate of 20 fps, which is twice the frame rate, may be set even though an object can be detected with sufficient accuracy if the frame rate is set to 10 fps. In this case, other problems such as resource exhaustion may occur due to unnecessary image processing.

[0022] Therefore, the information processing device 100 according to the embodiment has a modification unit that changes the number of images per unit time used to detect an object contained in an image captured by the imaging device 200 in accordance with the angle of view of the imaging device 200, and a detection unit that performs object detection using each of the images captured by the imaging device 200 in the modified number of images per unit time.

[0023] That is, the information processing device 100 according to the embodiment automatically adjusts the detection frame rate when detecting an object to a value corresponding to the angle of view of the imaging device 200 estimated from the image and information related to the imaging device 200. This allows the information processing device 100 to flexibly adjust the detection frame rate without depending on a specific detection frame rate, thereby improving the object detection accuracy.

[0024] [Configuration of information processing device] Next, the configuration of the information processing device 100 will be described with reference to Fig. 3. As shown in Fig. 3, the information processing device 100 has a communication unit 110, a control unit 120, and a storage unit 130. Note that each of these units may be held in a distributed manner in a plurality of devices. The processing of each of these units will be described below.

[0025] The communication unit 110 is realized by a NIC (Network Interface Card) or the like, and enables communication between an external device and the control unit 120 via an electric communication line such as a LAN (Local Area Network) or the Internet. For example, the communication unit 110 enables communication between the external device and the control unit 120.

[0026] The storage unit 130 is realized by a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 130 stores information about the imaging device 200, information about the imaging device 200, the frame rate, and other information necessary for changing the number of images per unit time. The information about the imaging device 200 includes information such as the model, identification number, angle of view, specifications (sensitivity, focal length, etc.), settings (resolution, storage format, etc.), captured images, coordinates where an object is detected, distance from the object, and the number of images per unit time (detection frame rate). The information stored in the storage unit 130 is not limited to the examples described above.

[0027] The control unit 120 is realized using a CPU (Central Processing Unit), an NP (Network Processor), an FPGA (Field Programmable Gate Array), etc., and executes a processing program stored in a memory. As shown in Fig. 3, the control unit 120 has an estimation unit 121, a change unit 122, and a detection unit 123. Each unit of the control unit 120 will be described below.

[0028] The estimation unit 121 estimates the angle of view of the imaging device 200 and outputs the estimation result to the change unit 122. For example, the estimation unit 121 estimates the angle of view of the imaging device 200 based on an image of a checkerboard captured by the imaging device 200. Details of the estimation method using a checkerboard will be described later.

[0029] In addition, the estimation unit 121 can input an image captured by the imaging device 200 into a trained model that has been trained to output an angle of view in response to an image input, and estimate the output angle of view as the angle of view of the imaging device 200.

[0030] The estimation unit 121 can also estimate the angle of view of the imaging device 200 based on information about the imaging device 200. For example, the estimation unit 121 estimates a range including coordinates where an object was previously detected by the imaging device 200 as the angle of view of the imaging device 200, as information about the imaging device 200. As another example, the estimation unit 121 can also estimate the angle of view of the target imaging device 200 by referring to the angle of view of other imaging devices 200 that have the same model number or common specifications or settings as the target imaging device 200. Note that the estimation unit 121 can also estimate the average value or median value of the angles of view of other imaging devices 200 that have the same model number or common specifications or settings as the target imaging device 200, or an angle of view that is commonly set between the other imaging devices 200, as the angle of view of the target imaging device 200.

[0031] The estimation unit 121 can also estimate the angle of view of the imaging device 200 using information on the distance to the object. For example, the estimation unit 121 estimates the angle of view of the imaging device 200 by multiplying the angle of view of the imaging device 200 estimated using the coordinates at which the object is detected by the imaging device 200 by a predetermined magnification corresponding to the distance to the object. As another example, the estimation unit 121 can also estimate the angle of view of the imaging device 200 by multiplying the angle of view of the imaging device 200 estimated from an image of a checkerboard captured by the imaging device 200 by a predetermined magnification corresponding to the distance to the object. Note that the predetermined magnification can be any value according to the purpose, such as a value that is smaller the closer the distance to the object is to the predetermined distance and a value that is larger the closer the distance to the object is to the predetermined distance.

[0032] The change unit 122 changes the number of images per unit time. Specifically, the change unit 122 changes the number of images per unit time used for detecting an object included in an image captured by the imaging device 200 according to the angle of view of the imaging device 200. For example, when the angle of view of the imaging device 200 is smaller than a predetermined angle of view, the change unit 122 increases the number of images per unit time used for detecting an object when the angle of view of the imaging device 200 is larger than the predetermined angle of view.

[0033] More specifically, when the angle of view of the imaging device 200 is smaller than a predetermined angle of view (e.g., 100 degrees), the change unit 122 changes the number of images per unit time used for object detection to a double value. On the other hand, when the angle of view of the imaging device 200 is larger than a predetermined angle of view (e.g., 100 degrees), the change unit 122 changes the number of images per unit time used for object detection to a half value.

[0034] In the above, an example has been shown in which the change unit 122 changes the number of images per unit time used for object detection to a value that is doubled or halved, but the change is not particularly limited as long as it changes the number of images per unit time used for object detection, such as a value obtained by adding or subtracting a predetermined value from the value before the change, a value obtained by multiplying or dividing the value before the change by a predetermined value, etc. In addition, any value according to the purpose can be used for the predetermined angle of view and the predetermined value.

[0035] As another example, the modification unit 122 can input the angle of view of the imaging device 200 into a trained model that has been trained to output the number of images per unit time in response to the input angle of view, and modify the output number of images per unit time as the number of images per unit time used to detect an object included in an image captured by the target imaging device 200.

[0036] The detection unit 123 executes object detection using each image of the changed number of images per unit time among the images captured by the imaging device 200. For example, the detection unit 123 determines for each image whether or not the object to be detected is included in each image of the changed number of images per unit time by the change unit 122 among the images captured by the imaging device 200, and detects the object when it is determined that the object is included a threshold number of times or more.

[0037] Next, the estimation process of estimating the angle of view by the estimation unit 121 and the change process of changing the number of images per unit time by the change unit 122 will be described with a specific example.

[0038] [Estimation process] The estimation process of the information processing device 100 according to the embodiment will be described with reference to Fig. 4 and Fig. 5. Fig. 4 and Fig. 5 are diagrams showing an example of the estimation process of the information processing device 100 according to the embodiment.

[0039] As an example, the estimation unit 121 estimates the angle of view of the camera from the rows, columns, number, etc. of the squares in an image captured from a predetermined position of a checkerboard with black squares. For example, as shown in Fig. 4, the estimation unit 121 estimates the angle of view of the camera from the range in which the black squares of the checkerboard are captured, such that if four rows of black squares are captured in an image captured from a predetermined position of a checkerboard with black squares, the angle of view is 90 degrees, and if six rows are captured, the angle of view is 120 degrees. Note that, in the above, an example has been described in which an image of a checkerboard with black squares is used to estimate the angle of view, but the image is not limited to this as long as it can be used to estimate the angle of view.

[0040] As another example, the estimation unit 121 estimates the angle of view of the imaging device 200 from past detection results as information related to the imaging device 200. For example, as shown in Fig. 5, when an obstacle is present right in front of the imaging device 200, the object cannot be detected in a part of the range (e.g., 120 degrees) that the imaging device 200 can capture. In such a case, the estimation unit 121 estimates the range (e.g., 90 degrees) that includes the point cloud of coordinates where the object was detected in the past as the angle of view.

[0041] Although an example in which an obstacle is present has been described above, even if no obstacle is present, the estimation unit 121 can perform a similar angle of view estimation process. As a result, when an obstacle such as a pillar or shelf is present, when a wall surface continues to be captured, or when there is a range through which a detection target object cannot physically pass, it is possible to exclude the area in which the object is not detected from the range that the imaging device 200 can capture, and estimate only the range in which the object can be detected as the angle of view.

[0042] As another example, the estimation unit 121 estimates the angle of view of the imaging device 200 by multiplying the angle of view of the imaging device 200 estimated by the method described with reference to Figs. 4 and 5 by a magnification factor according to the distance. Here, the predetermined magnification factor is set to a smaller value the shorter the distance to the object is than the predetermined distance, and a larger value the longer the distance is. For example, when the distance to the object is 1.5 m and the predetermined distance is 3 m, a predetermined magnification factor of 0.5 is used. For example, when the distance to the object is 6 m and the predetermined distance is 3 m, a predetermined magnification factor of 1.5 is used.

[0043] More specifically, the estimation unit 121 estimates that the angle of view of the imaging device 200 is 60 degrees, which is a value obtained by multiplying the angle of view of the imaging device 200, estimated based on the image, of 120 degrees by a magnification factor of 0.5 according to the distance. This makes it possible to estimate that the closer the distance to the object to be detected is, the smaller the angle of view of the imaging device 200 is, and that the farther the distance to the object to be detected is, the larger the angle of view of the imaging device 200 is.

[0044] [Change Processing] A change process of the information processing device 100 according to the embodiment will be described with reference to Figs. 6 to 8. Figs. 6 to 8 are diagrams showing an example of the change process of the information processing device 100 according to the embodiment. In this example, an example will be described in which an AI application, which is an application functioning as the information processing device 100, changes the number of images per unit time in accordance with the angle of view of the imaging device 200.

[0045] For example, as shown in FIG. 6(1), if the number of images per unit time (detection frame rate) used by the imaging device 200 to detect an object is 10 fps and the angle of view of the imaging device 200 is small, when a person crosses the area captured by the imaging device 200, the person can only be captured in three frames within the angle of view, and the person will pass before being captured the number of times required for detection (for example, four frames), and therefore the person cannot be detected.

[0046] In this way, since it is difficult to detect a person to be detected even if he or she passes through, the change unit 122 changes the number of images per unit time used for object detection to increase. For example, as shown in Fig. 6 (2), when the angle of view of the imaging device 200 is smaller than a predetermined angle of view (e.g., 100 degrees), the change unit 122 changes the number of images per unit time to a double value. In other words, the detection frame rate when detecting an object is changed from 10 fps to 20 fps.

[0047] 6(2), even if the angle of view of the imaging device 200 is small, the person can be detected because the person is captured within the angle of view in six frames when the person passes through an area captured by the imaging device 200. In this way, the information processing device 100 can prevent a decrease in detection accuracy even if the angle of view of the imaging device 200 is small by increasing the number of images per unit time used for object detection according to the angle of view.

[0048] Next, an example will be described in which there is a range in which an object cannot be detected within the range that the imaging device 200 can capture due to the presence of an obstacle in front of the imaging device 200. For example, as shown in Fig. 7(1), if the number of images per unit time used by the imaging device 200 to detect an object is 10 fps, and the angle of view is small due to the presence of a range in which an object cannot be detected, when a person passes in front of the imaging device 200, the person passes before being captured the number of times (for example, four frames) required for detection, and therefore the person cannot be detected.

[0049] In this way, since it is difficult to detect a person to be detected even if he or she passes by, the change unit 122 changes the number of images per unit time used for object detection to increase. For example, as shown in Fig. 7(2), when the angle of view of the imaging device 200 is smaller than a predetermined angle of view (e.g., 100 degrees), the change unit 122 changes the number of images per unit time used for object detection to a double value. In other words, the detection frame rate when detecting an object is changed from 10 fps to 20 fps.

[0050] 7(2), even if the angle of view of the imaging device 200 is small, the person can be detected because the person is captured within the angle of view in six frames when the person passes through an area captured by the imaging device 200. In this way, the information processing device 100 can prevent a decrease in detection accuracy even if the angle of view of the imaging device 200 is small by increasing the number of images per unit time used for object detection according to the angle of view.

[0051] Next, an example in which an unnecessarily high detection frame rate is set will be described. In Fig. 8, even though the angle of view of the imaging device 200 is large, 20 fps is set as the number of images per unit time used for object detection. For example, as shown in Fig. 8(1), before the change unit 122 changes the number of images per unit time used for object detection, when a person passes in front of the camera, 10 frames are captured, which is more than double the number of frames (e.g., 4 frames) required for detection.

[0052] In this way, when resources are wasted, the change unit 122 changes the number of images per unit time to decrease it. For example, as shown in Fig. 8 (2), the change unit 122 changes the number of images per unit time to half the value. In other words, the detection frame rate when detecting an object is changed from 20 fps to 10 fps.

[0053] As a result, it is possible to reduce resources by decreasing the number of images per unit time as shown in Fig. 8(2) from a state in which the angle of view of the imaging device 200 is large and the number of images per unit time is large as shown in Fig. 8(1). In this way, the information processing device 100 can improve resource efficiency for an AI application in which more resources than necessary are allocated to object detection by decreasing the number of images per unit time according to the angle of view.

[0054] [flowchart] Next, a flow of processing by the information processing device 100 will be described with reference to Fig. 9. Note that the following steps S101 to S104 may be executed in a different order. Also, among the following steps S101 to S104, some processing may be omitted.

[0055] First, the estimation unit 121 estimates the angle of view of the imaging device 200 (step S101). For example, the estimation unit 121 estimates the angle of view of the imaging device 200 based on an image. Also, for example, the estimation unit 121 estimates the angle of view of the imaging device 200 based on information related to the imaging device 200.

[0056] Next, the change unit 122 changes the number of images per unit time used for detecting an object included in an image captured by the imaging device 200 according to the angle of view of the imaging device 200 (step S102). For example, when the angle of view of the imaging device 200 is smaller than a predetermined angle of view, the change unit 122 changes the number of images per unit time to increase it.

[0057] Next, the detection unit 123 determines whether or not the object is included in each image of the number of images per unit time at least the threshold number of times (step S103). If the detection unit 123 determines that the object is not included in each image of the number of images per unit time at least the threshold number of times (step S103 "NO"), the information processing device 100 performs the process of step S103 again.

[0058] On the other hand, if the detection unit 123 determines that the object is included in each image of the number of images per unit time equal to or greater than the threshold number of times (step S103 "YES"), the detection unit 123 detects the object (step S104).

[0059] [effect] The information processing device 100 according to the embodiment includes a change unit 122 that changes the number of images per unit time used to detect an object included in an image captured by the imaging device 200 in accordance with the angle of view of the imaging device 200, and a detection unit 123 that executes object detection using each of the images captured by the imaging device 200 in the changed number of images per unit time. This allows the information processing device 100 to change the detection frame rate, which is the number of images per unit time used to detect an object, in accordance with the angle of view of the imaging device 200, and improve the object detection accuracy.

[0060] The information processing device 100 according to the embodiment includes an estimation unit 121 that estimates the angle of view of the imaging device 200 based on an image captured by the imaging device 200. As a result, the information processing device 100 estimates the angle of view of the imaging device 200 based on an image captured by the imaging device 200, and changes the detection frame rate, which is the number of images per unit time used to detect an object, according to the estimated angle of view of the imaging device 200, thereby making it possible to further improve the object detection accuracy.

[0061] The information processing device 100 according to the embodiment has an estimation unit 121 that estimates the angle of view of the imaging device 200 based on information related to the imaging device 200. As a result, the information processing device 100 estimates the angle of view of the imaging device 200 by excluding a range in which an object cannot be detected or by adjusting according to a distance or the like based on the information related to the imaging device 200, and changes a detection frame rate, which is the number of images per unit time used for object detection, according to the estimated angle of view of the imaging device 200, thereby making it possible to further improve the object detection accuracy.

[0062] The change unit 122 of the information processing device 100 according to the embodiment increases the number of images per unit time when the angle of view of the imaging device 200 is smaller than a predetermined angle of view. As a result, when the angle of view of the imaging device 200 is small, the information processing device 100 can greatly change the detection frame rate, which is the number of images per unit time used for object detection, to further improve the object detection accuracy.

[0063] The change unit 122 of the information processing device 100 according to the embodiment reduces the number of images per unit time when the angle of view of the imaging device 200 is larger than a predetermined angle of view. As a result, when the angle of view of the imaging device 200 is large, the information processing device 100 reduces the detection frame rate, which is the number of images per unit time used for object detection, to enable effective use of resources.

[0064] The modification unit 122 of the information processing device 100 according to the embodiment inputs the angle of view of the imaging device 200 into a trained model that has been trained to output the number of images per unit time in response to the input of the angle of view, and modifies the output number of images per unit time as the number of images per unit time used to detect objects included in images captured by the imaging device 200.

[0065] As a result, the information processing device 100 can use a model that has learned the relationship between the angle of view and the number of images per unit time to appropriately change the detection frame rate, which is the number of images per unit time used to detect an object, in accordance with the angle of view of the imaging device 200, thereby further improving the accuracy of object detection.

[0066] [program] It is also possible to create a program in which the processes executed by the information processing device 100 described in the above embodiment are written in a language executable by a computer. In this case, the same effects as those of the above embodiment can be obtained by having the computer execute the program. Furthermore, such a program may be recorded on a computer-readable recording medium, and the program recorded on the recording medium may be read and executed by a computer to realize the same processes as those of the above embodiment.

[0067] The information processing device 100 is realized, for example, by a computer system 1000 as shown in Fig. 10. The computer system 1000 has a CPU 1100, a RAM 1200, a ROM 1300, a HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

[0068] The CPU 1100 operates and controls each unit based on a program stored in the ROM 1300 or the HDD 1400. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer system 1000 is started up, programs that depend on the hardware of the computer system 1000, and the like.

[0069] The HDD 1400 stores programs executed by the CPU 1100, data used by the programs, etc. The communication interface 1500 receives data from other devices via the communication network NW and sends it to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the communication network NW.

[0070] The CPU 1100 controls output devices such as a display and a printer, and input devices such as a keyboard and a mouse, via the input / output interface 1600. The CPU 1100 acquires data from the input devices via the input / output interface 1600. The CPU 1100 also outputs generated data to the output devices via the input / output interface 1600.

[0071] The media interface 1700 reads a program or data stored in the recording medium 1800, and provides it to the CPU 1100 via the RAM 1200. The CPU 1100 loads the program from the recording medium 1800 onto the RAM 1200 via the media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase change rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0072] For example, when the computer system 1000 functions as the information processing device 100 of the present disclosure, the CPU 1100 of the computer system 1000 executes a program loaded onto the RAM 1200 to realize the function of the information processing device 100. The HDD 1400 stores data in the storage unit 130. The CPU 1100 of the computer system 1000 reads and executes these programs from the recording medium 1800, but as another example, the CPU 1100 may obtain these programs from another device via the communication network NW.

[0073] [others] Although various embodiments have been described in detail herein with reference to the drawings, these embodiments are merely examples and are not intended to limit the present invention to these embodiments. The features described herein can be realized in various ways, including various modifications and improvements based on the knowledge of those skilled in the art.

[0074] Furthermore, the above-mentioned "module (-er suffix, -or suffix)" can be read as a unit, a means, a circuit, a step, etc. For example, a communication module, a control module, and a storage module can be read as a communication unit, a control unit, and a storage unit, respectively. [Explanation of symbols]

[0075] 100 Information processing device 110 Communications Department 120 Control section 121 Estimation Department 122 Changes 123 Detection unit 130 Storage section 200 Imaging device

Claims

1. a change unit that changes the number of images per unit time used to detect an object included in an image captured by the imaging device in accordance with an angle of view of the imaging device; a detection unit that detects the object by using each image captured by the imaging device after changing the number of images per unit time; 13. An information processing device comprising:

2. The information processing apparatus according to claim 1 , further comprising an estimation unit that estimates an angle of view of the imaging device based on an image captured by the imaging device.

3. The information processing apparatus according to claim 1 , further comprising an estimation unit that estimates an angle of view of the imaging device based on information about the imaging device.

4. The information processing apparatus according to claim 1 , wherein the change section increases the number of images per unit time when the angle of view of the imaging device is smaller than a predetermined angle of view.

5. The information processing apparatus according to claim 1 , wherein the change section reduces the number of images per unit time when the angle of view of the imaging device is larger than a predetermined angle of view.

6. The angle of view of an imaging device is input to a trained model that has been trained to output the number of images per unit time in response to the input of the angle of view of the imaging device, and the output number of images per unit time is changed as the number of images per unit time used for detecting an object included in an image captured by the imaging device.

2. The information processing apparatus according to claim 1,

7. A method executed by an information processing device, comprising: a changing step of changing the number of images per unit time used for detecting an object included in an image captured by the imaging device in accordance with an angle of view of the imaging device; a detection step of detecting the object using each image captured by the imaging device according to the changed number of images per unit time; 13. An information processing method comprising:

8. a changing step of changing the number of images per unit time used for detecting an object included in an image captured by the imaging device in accordance with an angle of view of the imaging device; a detection step of detecting the object by using each image captured by the imaging device according to the changed number of images per unit time; An information processing program characterized by causing a computer to execute the above.

Images