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

Abstract

To obtain an information processing device, an information processing method, and an information processing program that can determine the occurrence status of predetermined events with higher accuracy. [Solution] The information processing device 10 includes a derivation unit 11B that derives the movement trajectory of a moving object in a target area based on a captured image obtained by photographing the target area, a determination unit 11C that determines the occurrence status of a predetermined event based on the movement trajectory derived by the derivation unit 11B and movement trajectories that were previously deemed false reports, and a presentation unit 11D that presents the determination result by the determination unit 11C.

Description

Technical Field

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

[0002] Conventionally, the following technologies have been available as technologies applicable for detecting the occurrence of a predetermined event caused by a moving body such as a vehicle, a pedestrian, or a traveling robot using a captured image obtained by capturing an image of a target region with an imaging device.

[0003] Patent Document 1 discloses an intruding object detection image processing system aimed at reducing the burden on a monitor.

[0004] This intruding object detection image processing system comprises: a television camera that captures an image of a monitoring area and outputs an image signal of the monitoring area; and detects an intruding object from the monitoring area included in the image signal input from the television camera, and outputs an alarm signal when an intruding object is detected. In the intruding object detection image processing system, when the detection alarm signal for the intruding object is a false detection, the false detection portion is removed from the monitoring area in the next detection of an intruding object, so that false detection in the same portion is eliminated and false detections are reduced. Prior Art Documents Patent Documents

[0005] Patent Document 1 Japanese Unexamined Patent Application Publication No. 2001-155263 Summary of the Invention Problems to be Solved by the Invention

[0006] However, the technology disclosed in Patent Document 1 allows the user to input whether an intruded object is correctly detected or incorrectly detected, thereby suppressing false detections within the same area. However, this suppresses all detection notifications within the same area, which means that it is not always possible to accurately determine the occurrence of an event (intrusion in the technology disclosed in Patent Document 1) for all target areas.

[0007] Furthermore, this issue can arise not only when monitoring human intrusion into a surveillance area, but also when determining the occurrence of events related to the movement of artificial objects such as vehicles and walking robots, or animals such as dogs and cats.

[0008] The present invention has been made in view of the above points, and aims to provide an information processing device, an information processing method, and an information processing program that can determine the occurrence status of predetermined events with higher accuracy. [Means for solving the problem]

[0009] The information processing apparatus of the present invention comprises: a derivation unit that derives the movement trajectory of a moving object in a target area based on a captured image obtained by photographing the target area; a determination unit that determines the occurrence status of a predetermined event based on the movement trajectory derived by the derivation unit and the movement trajectory that was previously deemed a false report; and a presentation unit that presents the determination result by the determination unit.

[0010] The information processing method of the present invention involves a computer deriving the movement trajectory of a moving object in a target area based on an image taken of the target area, determining the occurrence status of a predetermined event based on the derived movement trajectory and movement trajectories that were previously deemed false, and presenting the determination result.

[0011] The information processing program of the present invention causes a computer to perform the following processes: deriving the movement trajectory of a moving object in a target area based on an image taken of the target area; determining the occurrence status of a predetermined event based on the derived movement trajectory and movement trajectories that were previously deemed false reports; and presenting the determination result. [Effects of the Invention]

[0012] According to the present invention, it is possible to provide an information processing device, an information processing method, and an information processing program that can determine the occurrence status of predetermined events with higher accuracy. [Brief explanation of the drawing]

[0013] [Figure 1] This block diagram shows an example of the configuration of an information processing device according to the embodiment. [Figure 2] This is a block diagram showing an example of the functional configuration of an information processing apparatus according to the embodiment. [Figure 3] This is a schematic diagram showing an example of the configuration of a movement trajectory information database according to the first and third embodiments. [Figure 4] This is a schematic diagram showing an example of the configuration of the event information database according to the first and second embodiments. [Figure 5] This is a schematic diagram showing an example of the configuration of the output exclusion information database according to the embodiment. [Figure 6] This is a schematic diagram illustrating the information processing method according to the embodiment. [Figure 7] This is a flowchart showing an example of information processing according to the first embodiment. [Figure 8] This is a schematic diagram showing an example of the configuration of a movement trajectory information database according to the second embodiment. [Figure 9] This is a flowchart showing an example of information processing according to the second embodiment. [Figure 10] This is a schematic diagram showing an example of the configuration of the event information database according to the third embodiment. [Figure 11]It is a flowchart illustrating an example of information processing according to the third embodiment. Description of Embodiments

[0014] Hereinafter, embodiments for carrying out the present invention will be described in detail with reference to the drawings. In the present embodiment, a case where the information processing apparatus, information processing method, and information processing program according to the technology of the present disclosure are applied to determining the traveling state of a vehicle will be described. However, the present invention is not limited to this embodiment. For example, the technology of the present disclosure may be applied to determining the occurrence status of events related to movement of persons other than vehicle occupants such as pedestrians, walking robots, and animals such as dogs and cats.

[0015] First Embodiment FIG. 1 is a block diagram illustrating an example of the configuration of the information processing apparatus 10 according to the present embodiment.

[0016] The information processing apparatus 10 according to the present embodiment includes a CPU (Central Processing Unit) 11 serving as a computer, a memory 12 serving as a temporary storage area, a non-volatile storage unit 13, an input unit 14 such as a keyboard and a mouse, a display unit 15 such as a liquid crystal display, a medium read / write device (R / W) 16, and a communication interface (I / F) unit 18. The CPU 11, the memory 12, the storage unit 13, the input unit 14, the display unit 15, the medium read / write device 16, and the communication I / F unit 18 are connected to each other via a bus B. The medium read / write device 16 reads information recorded in the recording medium 17 and writes information to the recording medium 17.

[0017] The storage unit 13 according to the present embodiment is implemented by an HDD (Hard Disk Drive), an SSD (Solid State Drive), a flash memory, or the like. An information processing program 13A is stored in the storage unit 13 as a storage medium. The information processing program 13A is stored (installed) in the storage unit 13 when a recording medium 17 having the program 13A written thereon is set in a medium read-write device 16, and the medium read-write device 16 reads the program 13A from the recording medium 17. The CPU 11 appropriately reads the information processing program 13A from the storage unit 13, develops it in the memory 12, and sequentially executes processes included in the program 13A.

[0018] Furthermore, as shown in FIG. 1, an imaging device 30 is connected to the information processing apparatus 10 according to the present embodiment, and the CPU 11 can acquire data indicating a captured image obtained by imaging with the imaging device 30 (hereinafter referred to as "captured image data").

[0019] The imaging device 30 according to the present embodiment is provided such that a predetermined imaging target area (hereinafter referred to as "target area") for predetermined monitoring targets including roads, parking lots, intersections, and the like is included within the angle of view. Although the present embodiment exemplifies a case where only one imaging device 30 is connected to the information processing apparatus 10, it goes without saying that a plurality of imaging devices 30 may be connected to the information processing apparatus 10, and processing similar to that of the present embodiment can be performed on captured images obtained from the plurality of imaging devices 30.

[0020] Although the imaging device 30 according to the present embodiment is a camera that captures color moving images, the present invention is not limited to this configuration. For example, a camera that captures monochrome moving images may be used as the imaging device 30. Further, depending on the speed of the target moving object, a camera that captures still images may be used as the imaging device 30.

[0021] Furthermore, the storage unit 13 according to this embodiment stores a movement trajectory information database 13B, an event information database 13C, and an output exclusion information database 13D. Details of these databases will be described later.

[0022] Next, the functional configuration of the information processing device 10 according to this embodiment will be described with reference to Figure 2. Figure 2 is a functional block diagram showing an example of the functional configuration of the information processing device 10 according to this embodiment.

[0023] As shown in Figure 2, the information processing device 10 according to this embodiment includes an acquisition unit 11A, a derivation unit 11B, a determination unit 11C, a presentation unit 11D, and a reception unit 11E. The CPU 11 of the information processing device 10 executes an information processing program 13A, and the CPU 11 functions as the acquisition unit 11A, the derivation unit 11B, the determination unit 11C, the presentation unit 11D, and the reception unit 11E.

[0024] In this embodiment, the acquisition unit 11A acquires captured image data from the shooting device 30, which shows the captured image obtained by shooting the target area.

[0025] Furthermore, the derivation unit 11B according to this embodiment derives the movement trajectory of a moving object in the target area based on the captured image data obtained by the acquisition unit 11A, and registers the movement trajectory information indicating the derived movement trajectory in the storage unit 13.

[0026] Furthermore, the determination unit 11C according to this embodiment determines the occurrence status of a predetermined event based on the movement trajectory derived by the derivation unit 11B and the movement trajectory that was previously deemed a false alarm.

[0027] The presentation unit 11D in this embodiment then presents the determination result from the determination unit 11C. In this embodiment, the presentation unit 11D uses display by the display unit 15 to present various information, but it is not limited to this form. For example, the presentation unit 11D may use printing by an image forming apparatus or audio presentation by a sound generation device to present various information.

[0028] Here, the determination unit 11C according to this embodiment determines the occurrence status of the above event based on the similarity between the movement trajectory derived by the derivation unit 11B and movement trajectories that were previously identified as false alarms.

[0029] In this embodiment, the average difference of each coordinate value between the newly derived movement trajectory information and the movement trajectory information registered in the past is applied as the similarity measure, but the embodiment is not limited to this form. For example, the similarity measure could be applied to the two pieces of movement trajectory information using DTW (Dynamic Time Warping), CCF (Cross-Correlation Function), or a comparison of cross-correlation.

[0030] Furthermore, the receiving unit 11E according to this embodiment receives information from the user indicating whether the judgment result presented by the presentation unit 11D is correct or not. If the receiving unit 11E indicates that the received information is incorrect, that is, if the presented judgment result was a false report, it registers information to that effect in the storage unit 13.

[0031] In this embodiment, the information processing device 10 uses a vehicle as the moving object, and at least one (all of them in this embodiment) of the following events are applied: stopping, avoiding, speeding, and driving at a slow speed.

[0032] Furthermore, a vehicle's avoidance maneuver can be determined by determining whether its movement trajectory crossed a road lane and then returned to the same lane. A vehicle's stop can be determined by determining whether the amount of movement in its movement trajectory is 0 (zero). A vehicle's slow speed can be determined by determining whether the amount of movement per predetermined time in its movement trajectory exceeds 0 (zero) and is below a predetermined lower threshold. In addition, a vehicle's speed can be determined by determining whether the amount of movement per predetermined time in its movement trajectory exceeds a predetermined upper threshold.

[0033] Next, with reference to Figure 3, the movement trajectory information database 13B according to this embodiment will be described. Figure 3 is a schematic diagram showing an example of the configuration of the movement trajectory information database 13B according to this embodiment.

[0034] The movement trajectory information database 13B according to this embodiment stores the aforementioned movement trajectory information of the vehicle shown in the captured image data, and as shown in Figure 3, the frame number, object ID (Identification), object size, and object position information are stored in association with each other.

[0035] The frame number mentioned above is information indicating the frame number of the frame in which the vehicle is shown in the moving image data, and the object ID mentioned above is information that is assigned to each vehicle individually in order to identify the vehicle shown in the image of the corresponding frame number.

[0036] Furthermore, the object size mentioned above is information indicating the dimensions of the corresponding vehicle, and in this embodiment, it is information indicating the height and width of the circumscribing rectangular frame of the corresponding vehicle. In this embodiment, the number of pixels of the height and width of the circumscribing rectangular frame of the corresponding vehicle in the corresponding captured image are applied as the object size, but the embodiment is not limited to this form. For example, the actual size of the corresponding vehicle estimated from the corresponding captured image may be applied as the object size.

[0037] Furthermore, the object position described above is information indicating the position of the corresponding vehicle. In this embodiment, information indicating the X and Y coordinates of the predetermined position (center position in this embodiment) of the corresponding vehicle in a two-dimensional coordinate system with the origin (0,0) set at a predetermined position in the captured image (in this embodiment, the position of the lower left corner point in the captured image). However, it goes without saying that the invention is not limited to this form.

[0038] To avoid confusion, the movement trajectory information database 13B shown in Figure 3 illustrates the case where only one vehicle is visible in each frame image, but it is not limited to this form. If multiple vehicles are visible in each frame image, multiple sets of object IDs, object sizes, and object positions will be sequentially stored in the movement trajectory information database 13B for each frame image.

[0039] Next, the event information database 13C according to this embodiment will be described with reference to Figure 4. Figure 4 is a schematic diagram showing an example of the configuration of the event information database 13C according to this embodiment.

[0040] The event information database 13C according to this embodiment stores information about the event (hereinafter referred to as "event information") that is presented to the user by the presentation unit 11D when the above-mentioned event (in this embodiment, vehicle stopping, avoidance, speeding, and slow driving) occurs. As shown in Figure 4, the event ID, event name, frame number, object size, and object position information are stored in association with each other.

[0041] The above event ID is information assigned to each event individually in order to identify the anticipated event, and the above event name is information indicating the name of the corresponding event. Furthermore, the above frame number, object size, and object position are the same information as the frame number, object size, and object position registered in the aforementioned movement trajectory information database 13B for the vehicle in which the corresponding event occurred.

[0042] In other words, the event information database 13C according to this embodiment is a database in which the registered information itself becomes the information presented to the user.

[0043] Next, with reference to Figure 5, the output exclusion information database 13D according to this embodiment will be described. Figure 5 is a schematic diagram showing an example of the configuration of the output exclusion information database 13D according to this embodiment.

[0044] The output exclusion information database 13D according to this embodiment stores information (hereinafter referred to as "output exclusion information") to exclude further presentations of the occurrence of any event to the user if the presentation by the presentation unit 11D was a false alarm, even if any event occurs and is presented to the user. As shown in Figure 5, the event name, frame number, object size, and object position information are stored in association with each other.

[0045] The event name, frame number, object size, and object position mentioned above are the same as the event name, frame number, object size, and object position registered in the event information database 13C described above.

[0046] In other words, the output exclusion information database 13D according to this embodiment is a database in which the registered information itself serves as the criterion for excluding it from being presented to the user.

[0047] Next, an overview of the information processing method according to this embodiment will be described with reference to Figure 6. Figure 6 is a schematic diagram used to explain the information processing method according to this embodiment. Figure 6 illustrates the case where "evasive maneuvering" occurs as one of the events described above.

[0048] As shown in Figure 6, in the information processing method according to this embodiment, the acquisition unit 11A acquires captured image data indicating the target area from the imaging device 30.

[0049] Next, in the information processing method according to this embodiment, the derivation unit 11B detects the moving vehicle 34A from the captured image 32A shown in the captured image data acquired by the acquisition unit 11A using object detection processing, and tracks the detected vehicle 34A using object tracking processing to derive the movement trajectory 36A of the vehicle 34A. Then, the derivation unit 11B registers the movement trajectory information showing the derived movement trajectory 36A in the movement trajectory information database 13B.

[0050] In this embodiment, the object detection process uses a pre-trained Convolutional Neural Network (CNN) model to detect vehicles, but the embodiment is not limited to this form. For example, the object detection process may be performed using a learning model other than a CNN, or it may be performed using a combination of Histgrams of Oriented Gradients (HOG) features and Support Vector Machine (SVM).

[0051] Furthermore, in this embodiment, the object tracking process is performed by comparing the similarity of features extracted by a pre-trained CNN model, but the system is not limited to this form. For example, object tracking processes using optical flow or particle filters may also be applied.

[0052] As described above, in this embodiment, the object detection process and the object tracking process are executed as separate processes, but the embodiment is not limited to this configuration. For example, the object detection process and the object tracking process may be executed as a single process.

[0053] Next, in the information processing method according to this embodiment, the determination unit 11C determines, based on the movement trajectory 36A derived by the derivation unit 11B, whether or not one of the predetermined types of events (in this embodiment, vehicle stopping, avoidance, speeding, and slow driving) has occurred in the vehicle 34A. Furthermore, if the determination unit 11C determines that one of the events has occurred, it determines the type of event that occurred as described above and registers the event information described above in the event information database 13C.

[0054] In the information processing method according to this embodiment, if the determination unit 11C determines that any event has occurred, the presentation unit 11D controls the display unit 15 to display (output) information indicating that the event has been detected, along with the corresponding captured image 32A. Therefore, the user of the information processing device 10 can refer to the display screen of the display unit 15 to understand that the above event has occurred and to a captured image that shows the circumstances thereof.

[0055] The user then determines whether the event that occurred was a non-problematic event (hereinafter referred to as an "excluded output event"). If the user determines that it was an excluded output event, they input information via the input unit 14 indicating that the output of the event was a false alarm (hereinafter referred to as "false alarm notification information"). In response to this input, the determination unit 11C registers the above-mentioned excluded output information regarding the event that occurred in the excluded output information database 13D. In the example shown in Figure 6, a vehicle 34A's avoidance maneuver was detected, but this avoidance maneuver was to bypass a road cone 38, and is therefore considered not problematic.

[0056] If the event that occurred was not an event that should be excluded from output, that is, if the event that occurred was a problematic event, the user will perform the same processing as in conventional technology to address the problem.

[0057] From this point forward, in the information processing method according to this embodiment, the derivation unit 11B similarly detects the moving vehicle 34B from the captured image 32B shown by the captured image data acquired by the acquisition unit 11A, and if the determination unit 11C determines that any type of event has occurred, the similarity between the movement trajectory 36B obtained in that process and the movement trajectory 36A on which the output exclusion information described above is registered is calculated as described above.

[0058] In the information processing method according to this embodiment, the determination unit 11C determines whether the calculated similarity is equal to or greater than a predetermined threshold TH. If it is determined that the similarity is equal to or greater than the threshold TH, the event that occurred in vehicle 34B is considered to be a non-problematic event, and the event information related to that event is not registered in the event information database 13C. As a result, the presentation unit 11D excludes the presentation (output) of the occurrence of this event to the user.

[0059] Next, with reference to Figure 7, the operation of the information processing device 10 according to this embodiment during the execution of information processing will be explained. Figure 7 is a flowchart showing an example of the flow of information processing according to this embodiment. Information processing according to this embodiment is executed when instruction information indicating that the user of the information processing device 10 should execute it is input via the input unit 14.

[0060] In step 100 shown in Figure 7, the CPU 11 acquires captured image data from the imaging device 30.

[0061] In step 102, the CPU 11 performs the object detection process described above on the captured image (hereinafter simply referred to as "captured image") indicated by the acquired captured image data. In step 104, the CPU 11 uses the results of the object detection process to determine whether or not a vehicle as a moving object is visible in the captured image. If the determination is negative, the system proceeds to step 126; if the determination is positive, the system proceeds to step 106.

[0062] In step 106, the CPU 11 performs the object tracking process described above on the vehicle detected by the processing in step 102, thereby tracking the detected vehicle (hereinafter referred to as the "tracked vehicle") for a predetermined period (2 seconds in this embodiment). In step 108, the CPU 11 obtains movement trajectory information showing the movement trajectory of the tracked vehicle from the information obtained by the object tracking process and registers it in the movement trajectory information database 13B.

[0063] In step 110, the CPU 11 uses the registered movement trajectory information to determine whether any of the above events have occurred. If the determination is negative, the system proceeds to step 126; if the determination is positive, the system proceeds to step 112. In step 112, the CPU 11 obtains all output exclusion information by reading it from the output exclusion information database 13D.

[0064] In step 114, the CPU 11 calculates the similarity between the movement trajectory information obtained by the process in step 108 and the movement trajectory information indicated by the output exclusion information obtained by the process in step 112, for all acquired output exclusion information, as described above. In step 116, the CPU 11 determines whether at least one of the calculated similarities is less than the threshold TH. If the determination is negative, the CPU proceeds to step 120; if the determination is positive, the CPU proceeds to step 118.

[0065] In step 118, the CPU 11 registers (saves) the aforementioned event information regarding the tracked vehicle in the event information database 13C. In step 120, if the CPU 11 has registered new event information in the event information database 13C, it controls the display unit 15 to display (output) information indicating that the event described in the event information has been detected, along with the corresponding captured image. As described above, the user then determines whether the displayed event is an event that should not be output, and if it is an event that should not be output, inputs false alarm notification information.

[0066] Therefore, in step 122, the CPU 11 determines whether or not false alarm information has been entered by the user. If the determination is negative, the system proceeds to step 126; if the determination is positive, the system proceeds to step 124. In step 124, the CPU 11 updates the output exclusion information database 13D by newly registering the aforementioned output exclusion information for the tracked vehicle in the output exclusion information database 13D.

[0067] In step 126, the CPU 11 determines whether a predetermined termination timing has arrived to end the information processing. If the determination is negative, the CPU returns to step 100; if the determination is positive, the information processing ends. In this embodiment, the termination timing is the timing at which instruction information to terminate the information processing is input by the user via the input unit 14, but it goes without saying that the system is not limited to this configuration.

[0068] As explained above, according to this embodiment, based on the captured image obtained by photographing the target area, the movement trajectory of a moving object in the target area is derived, and based on the derived movement trajectory and movement trajectories that were previously identified as false alarms, the occurrence status of a predetermined event is determined and the determination result is presented. Therefore, compared to the technology that excludes areas of false detection pointed out by the user from the monitoring area, the occurrence status of a predetermined event can be determined with higher accuracy.

[0069] Furthermore, according to this embodiment, the occurrence status of the above-mentioned event is determined based on the similarity between the derived movement trajectory and movement trajectories that were previously identified as false alarms. Therefore, the occurrence status of the event can be determined with higher accuracy compared to the case where the occurrence status of the above-mentioned event is determined without using the similarity.

[0070] Furthermore, according to this embodiment, information indicating whether the presented judgment result is correct or incorrect is received from the user. Therefore, compared to cases where information indicating whether the presented judgment result is correct or incorrect is received from a source other than the user, more accurate information can be obtained as information indicating whether the judgment result is correct or incorrect.

[0071] Furthermore, according to this embodiment, a vehicle is used as the moving object, and at least one of the above events—stopping, avoiding, speeding, and driving at a low speed—is applied to the vehicle. Therefore, with respect to the events applied to the vehicle, the effects of the technology of this disclosure can be enjoyed.

[0072] [Second Embodiment] In this embodiment, an example of a configuration in which the presentation of the determination result by the presentation unit 11D is prohibited when predetermined prohibition conditions are met will be described.

[0073] In other words, the display unit 11D according to this embodiment prohibits the display of the judgment result if it matches a predetermined prohibition condition. In this embodiment, the prohibition condition is that the vehicle is a vehicle of a type in which the occurrence of the above event is permitted, such as an emergency vehicle such as an ambulance or police vehicle, or a work vehicle such as a tow truck, but the embodiment is not limited to this form. For example, the prohibition condition may be that the vehicle is of a size in which the occurrence of the above event is permitted. In other words, various conditions that match the external characteristics of a vehicle in which the occurrence of the event is permitted can be applied as prohibition conditions.

[0074] The configuration of the information processing device 10 according to this embodiment differs from that of the first embodiment only in the function of the presentation unit 11D and the configuration of the movement trajectory information database 13B. Therefore, first, the configuration of the movement trajectory information database 13B according to this embodiment will be described with reference to Figure 8.

[0075] As shown in Figure 8, the movement trajectory information database 13B according to this embodiment differs from the movement trajectory information database 13B according to the first embodiment only in that a vehicle type ID has been newly added.

[0076] The above vehicle type ID is information assigned to each vehicle type in order to individually identify the vehicle type indicated by the corresponding object ID. In other words, the information processing device 10 according to this embodiment recognizes the vehicle type of the tracked vehicle and registers the vehicle type ID assigned to the recognized vehicle type as movement trajectory information in the movement trajectory information database 13B.

[0077] Next, with reference to Figure 9, the operation of the information processing device 10 according to this embodiment during the execution of information processing will be explained. Figure 9 is a flowchart showing an example of the flow of information processing according to this embodiment. The information processing according to this embodiment is also executed when instruction information indicating that the user of the information processing device 10 should execute it is input via the input unit 14. In the flowchart shown in Figure 9, steps that perform the same processing as the flowchart shown in Figure 7 are given the same step numbers as in Figure 7, and their explanations are omitted. Furthermore, in order to avoid confusion, this explanation will describe the case in which a vehicle type ID (hereinafter referred to as "set vehicle type ID") indicating the type of vehicle in which the occurrence of the above event is permitted is set in advance.

[0078] As shown in Figure 9, the information processing according to this embodiment differs from the information processing according to the first embodiment only in that the conditional judgment process in step 109 is added.

[0079] In other words, in step 109, the CPU 11 determines whether the tracked vehicle meets the above prohibition condition (in this embodiment, the condition that the vehicle type of the tracked vehicle is included in the vehicle type indicated by the set vehicle type ID). If the determination is positive, the CPU proceeds to step 126; otherwise, the CPU proceeds to step 110.

[0080] As a result of this conditional branching in step 109, if the pursuing vehicle meets a predetermined prohibition condition, the determination unit 11C will not display the determination result.

[0081] As explained above, according to this embodiment, the presentation of the judgment result is prohibited if the predetermined prohibition conditions are met. Therefore, it is possible to achieve the same effects as in the first embodiment, while suppressing the presentation of unnecessary judgment results.

[0082] In this embodiment, we have described a case where a single condition is applied as a prohibition condition for the technology disclosed herein, but this is not limited to this. For example, multiple conditions may be combined and applied as prohibition conditions for the technology disclosed herein.

[0083] [Third Embodiment] In this embodiment, an example of a configuration in which the determination unit 11C performs determination according to predetermined environmental conditions will be described.

[0084] In other words, the determination unit 11C according to this embodiment makes its own determinations based on predetermined environmental conditions. In this embodiment, time of day is applied as the environmental condition, but the system is not limited to this form. For example, the type of weather, whether or not road construction is occurring, etc., may be applied as the environmental condition. By applying various environmental conditions in this way, it becomes possible to, for example, exclude the notification of avoidance when lane closures are in place due to snow or road construction, and notify the driver of the occurrence of avoidance after the lane closures are lifted.

[0085] The configuration of the information processing device 10 according to this embodiment differs from that of the first embodiment only in the function of the determination unit 11C and the configuration of the output exclusion information database 13D. Therefore, first, the configuration of the output exclusion information database 13D according to this embodiment will be described with reference to Figure 10.

[0086] As shown in Figure 10, the output exclusion information database 13D according to this embodiment differs from the output exclusion information database 13D according to the first embodiment only in that the output exclusion information is registered by time period.

[0087] Next, with reference to Figure 11, the operation of the information processing device 10 according to this embodiment during the execution of information processing will be explained. Figure 11 is a flowchart showing an example of the flow of information processing according to this embodiment. The information processing according to this embodiment is also executed when instruction information indicating that the user of the information processing device 10 should execute it is input via the input unit 14. In the flowchart shown in Figure 11, steps that perform the same processing as those shown in the flowchart in Figure 7 are given the same step numbers as in Figure 7, and their explanations are omitted.

[0088] As shown in Figure 11, the information processing according to this embodiment differs from the information processing according to the first embodiment only in that the process of reading output exclusion information from the output exclusion information database 13D in step 112 is replaced by the process in step 113.

[0089] In other words, in step 113, the CPU 11 reads out output exclusion information from the output exclusion information database 13D that matches the environmental conditions (in this embodiment, time period) at that time.

[0090] By narrowing down the output exclusion information in step 113, the output exclusion information obtained under similar environmental conditions will be used in subsequent processing.

[0091] As explained above, according to this embodiment, the above determination is performed according to predetermined environmental conditions. Therefore, it is possible to achieve the same effects as in the first embodiment, and as a result of being able to perform the determination according to the same environmental conditions, the occurrence status of predetermined events can be determined with higher accuracy.

[0092] In this embodiment, the case in which a single condition is applied as the environmental condition for the technology of this disclosure has been described, but the invention is not limited to this. For example, multiple conditions may be combined and applied as the environmental condition for the technology of this disclosure.

[0093] Furthermore, while the above embodiments described cases where only the vehicle's movement trajectory is applied as a parameter for calculating similarity, the invention is not limited to this. For example, in addition to the vehicle's movement trajectory, the vehicle's speed may also be applied as a parameter for calculating similarity.

[0094] Furthermore, while the embodiments described above exemplify the phenomena of the technology of this disclosure as vehicle stopping, avoidance maneuvers, speeding, and slow driving, the technology is not limited to these. For example, driving in the wrong direction, making a U-turn, crossing a road, and swerving can also be exemplified as phenomena of the technology of this disclosure.

[0095] Furthermore, while the above embodiments describe cases in which the movement trajectory information database 13B, the event information database 13C, and the output exclusion information database 13D are registered in the information processing device 10, the system is not limited to this. For example, at least one of these databases may be registered in a device other than the information processing device 10.

[0096] Furthermore, the database configurations shown in each of the above embodiments are merely examples, and it goes without saying that some information may be deleted or new information may be added.

[0097] Furthermore, the flowcharts illustrating the information processing shown in each of the above embodiments are merely examples, and it goes without saying that the processing order of each step can be changed, some steps can be deleted, or new steps can be added.

[0098] Furthermore, in each of the above embodiments, the hardware structure of the processing unit that executes the acquisition unit 11A, the derivation unit 11B, the determination unit 11C, the presentation unit 11D, and the reception unit 11E can be any of the following types of processors. As mentioned above, these types of processors include a CPU, which is a general-purpose processor that executes software (programs) and functions as a processing unit, as well as programmable logic devices (PLDs), such as FPGAs (Field-Programmable Gate Arrays), which are processors whose circuit configuration can be changed after manufacturing, and dedicated electrical circuits, such as ASICs (Application Specific Integrated Circuits), which are processors with circuit configurations specifically designed to execute specific processes.

[0099] The processing unit may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the processing unit may consist of a single processor.

[0100] Examples of configuring a processing unit with a single processor include, firstly, a configuration where one or more CPUs and software combine to form a single processor, as is common in client and server computers, and this processor functions as the processing unit. Secondly, a configuration using a processor that realizes the functions of the entire system, including the processing unit, on a single IC (Integrated Circuit) chip, as is common in System-on-a-Chip (SoC) systems. Thus, the processing unit is configured, in terms of hardware structure, using one or more of the above-mentioned types of processors.

[0101] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits, which are combinations of circuit elements such as semiconductor devices.

[0102] The following additional information is disclosed regarding the above-described embodiments.

[0103] [Note 1] A derivation unit that derives the movement trajectory of a moving object in the target area based on the captured image obtained by photographing the target area, A determination unit determines the occurrence status of a predetermined event based on the movement trajectory derived by the derivation unit and the movement trajectory that was previously deemed a false report, A display unit that displays the determination result from the determination unit, Equipped with an information processing device. [Note 2] The determination unit determines the occurrence status of the event based on the similarity between the movement trajectory derived by the derivation unit and the movement trajectory that was previously deemed a false report. The information processing device described in Appendix 1. [Note 3] A receiving unit that receives information from the user indicating whether the judgment result presented by the presentation unit is correct or not, An information processing apparatus according to Appendix 1 or Appendix 2, further comprising the above. [Note 4] The aforementioned moving object is a vehicle, The aforementioned event is at least one of the following: stopping, avoiding, speeding, and driving slowly. An information processing device as described in any one of the appendices 1 to 3. [Note 5] The display unit prohibits the display of the judgment result if the predetermined prohibition conditions are met. An information processing device as described in any one of the appendices 1 through 4. [Note 6] The determination unit performs the determination according to predetermined environmental conditions. An information processing device as described in any one of the appendices 1 through 5. [Note 7] Computers Based on the captured image obtained by photographing the target area, the movement trajectory of the moving object in the target area is derived. Based on the derived movement trajectory and the movement trajectory that was previously deemed a false alarm, the occurrence status of a predetermined event is determined. Present the judgment result. An information processing method that performs a process. [Note 8] Based on the captured image obtained by photographing the target area, the movement trajectory of the moving object in the target area is derived. Based on the derived movement trajectory and the movement trajectory that was previously deemed a false alarm, the occurrence status of a predetermined event is determined. Present the judgment result. An information processing program that instructs a computer to perform a task. [Explanation of Symbols]

[0104] 10 Information Processing Devices 11 CPU 11A Acquisition Department 11B Derivation part 11C Judgment section 11D Presentation section 11E Reception Department 12 memory 13 Storage section 13A Information Processing Program 13B Movement Trajectory Information Database 13C Event Information Database 13D Output Exclusion Information Database 14 Input section 15 Display 16. Media reading / writing device 17 Recording media 18 Communication I / F Section 30 Imaging device Images taken with 32A and 32B. Vehicles 34A and 34B 36A, 36B movement trajectory 38 Road cone 90 Information Processing Systems

Claims

1. A derivation unit that derives the movement trajectory of a moving object in the target area based on the captured image obtained by photographing the target area, A determination unit determines the occurrence status of a predetermined event based on the movement trajectory derived by the derivation unit and the movement trajectory that was previously deemed a false report, A display unit that displays the determination result from the determination unit, Equipped with an information processing device.

2. The determination unit determines the occurrence status of the event based on the similarity between the movement trajectory derived by the derivation unit and the movement trajectory that was previously deemed a false report. The information processing apparatus according to claim 1.

3. A receiving unit that receives information from the user indicating whether the judgment result presented by the presentation unit is correct or not, An information processing apparatus according to claim 1 or claim 2, further comprising the above.

4. The aforementioned moving object is a vehicle, The aforementioned event is at least one of the following: stopping, avoiding, speeding, and driving slowly. The information processing apparatus according to claim 1 or claim 2.

5. The display unit prohibits the display of the judgment result if the predetermined prohibition conditions are met. The information processing apparatus according to claim 1 or claim 2.

6. The determination unit performs the determination according to predetermined environmental conditions. The information processing apparatus according to claim 1 or claim 2.

7. Computers Based on the captured image obtained by photographing the target area, the movement trajectory of the moving object in the target area is derived. Based on the derived movement trajectory and the movement trajectory that was previously deemed a false alarm, the occurrence status of a predetermined event is determined. Present the judgment result. An information processing method that performs a process.

8. Based on the captured image obtained by photographing the target area, the movement trajectory of the moving object in the target area is derived. Based on the derived movement trajectory and the movement trajectory that was previously deemed a false alarm, the occurrence status of a predetermined event is determined. Present the judgment result. An information processing program that instructs a computer to perform a task.

Images