Monitoring device, monitoring system, and monitoring method

Abstract

In a monitoring system using an EVS as a monitoring camera, a sufficient power saving effect can be obtained. The monitoring device includes: an image acquisition unit that acquires image data indicating a change in intensity of incident light; a region determination unit that determines, in the field of view of the image acquisition unit, a first region in which monitoring is to be performed and a second region in which monitoring is not to be performed; and a monitoring unit that outputs a monitoring result of the moving object on the basis of the image data acquired by the image acquisition unit in the first region.

Description

Technical Field

[0001] The invention relates to a monitoring device, a monitoring system and a monitoring method. Background Art

[0002] Among image sensors, event-based vision sensors (EVS) that detect changes in brightness of each pixel are known. In addition, for example, cameras are sometimes installed on vehicles for the purpose of theft prevention.

[0003] <Prior Art Literature>

[0004] <Patent Documents>

[0005] Patent Document 1: International Publication No. 2022 / 201973

[0006] Patent Document 2: (Japanese) Patent Publication No. 2023-009057

[0007] Patent Document 3: (Japanese) Patent Publication No. 2023-061207

[0008] Patent Document 4: (Japanese) Patent Publication No. 2022-163480

[0009] Patent Document 5: International Publication No. 2022 / 190470

[0010] Patent Document 6: (Japanese) Patent Publication No. 2014-211734

[0011] Patent Document 7: (Japanese) Patent Publication No. 2012-044404 Summary of the invention

[0012] <Problems to be Solved by the Invention>

[0013] When the vehicle's engine is stopped, the various devices on board the vehicle operate on the vehicle's battery. However, due to the limited capacity of the vehicle's battery, the long-term monitoring of the vehicle's camera is sometimes limited.

[0014] In this regard, it is possible to consider using an event-based visual sensor (hereinafter referred to as EVS) as a surveillance camera to achieve energy saving of the surveillance system. However, when the EVS is used as a surveillance camera, for example, when there are moving objects such as pedestrians or moving vehicles in the field of view of the surveillance camera, the surveillance system is activated, and sometimes sufficient power saving effect cannot be achieved.

[0015] One embodiment of the present invention has been made in view of the above-mentioned problem, and can obtain a sufficient power saving effect in a monitoring system using an EVS as a monitoring camera.

[0016] <Methods used to solve the problem>

[0017] In order to solve the above-mentioned problem, a monitoring device according to an embodiment of the present invention includes: an image acquisition unit, which acquires image data representing changes in the intensity of incident light; an area determination unit, which determines a first area to be monitored and a second area not to be monitored in the field of view of the image acquisition unit; and a monitoring unit, which outputs a monitoring result of a moving object based on the image data acquired by the image acquisition unit in the first area.

[0018] <Effects of the Invention>

[0019] According to the embodiment of the present invention, a sufficient power saving effect can be obtained in a monitoring system using an EVS as a monitoring camera. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a diagram showing an example of a system configuration of a monitoring system according to an embodiment.

[0021] Figure 2 This is a diagram for explaining the outline of processing in one embodiment.

[0022] Figure 3 FIG. 1 is a diagram showing an example of a functional configuration of a monitoring system according to an embodiment.

[0023] Figure 4 It is a diagram showing a configuration example of an EVS according to one embodiment.

[0024] Figure 5 FIG. 2 is a diagram showing an example of a functional configuration of a monitoring system according to an embodiment.

[0025] Figure 6 This is a flowchart showing an example of monitoring processing according to the first embodiment.

[0026] Figure 7 This is a flowchart showing an example of the area determination process according to the first embodiment.

[0027] Figure 8 This is a flowchart showing an example of suspicious person detection processing according to the first embodiment.

[0028] Fig. 9 This is a diagram for explaining the area change process according to the second embodiment.

[0029] Fig.10 This is a flowchart showing an example of the area change process according to the second embodiment.

[0030] Fig.11 This is a diagram showing an example of a system configuration of a monitoring system according to a third embodiment.

[0031] Fig.12 This is a diagram showing an example of a usage scenario of a monitoring system according to one embodiment.

[0032] Fig.13 This is a diagram showing an example of the hardware configuration of a computer according to one embodiment. DETAILED DESCRIPTION

[0033] Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[0034] <System Structure>

[0035] Figure 1 FIG. 1 is a diagram showing an example of a system configuration of a monitoring system according to an embodiment. Figure 1 In the example of FIG. 1 , the monitoring system 1 includes a monitoring device 100 and an information processing device 101 mounted on a vehicle 10 such as a car.

[0036] The monitoring device 100 is a monitoring camera that uses an event-based vision sensor (EVS) to obtain EVS image data representing brightness changes in the interior of the vehicle 10, or a device including the monitoring camera. The event-based vision sensor (hereinafter referred to as EVS) is an image sensor that detects brightness changes in each pixel and combines only the changed data with "coordinates" and "time information" and outputs it. In addition, EVS is also called other names such as a dynamic vision sensor.

[0037] exist Figure 1 In the example of FIG. 1 , the monitoring device 100 is disposed at the rear of the interior of the vehicle 10, and acquires EVS image data (hereinafter referred to as image data) of the interior of the vehicle from the rear of the interior. In addition, the monitoring device 100 monitors moving objects in the interior of the vehicle 10 based on the acquired image data, and outputs the monitoring results of the moving objects to the information processing device 101.

[0038] The information processing device 101 is a computer that executes a predetermined process based on the monitoring result of the moving object output by the monitoring device 100. The information processing device 101 may be an electronic control unit (ECU: Electronic Control Unit) included in the vehicle 10, or may be a computer different from the electronic control unit included in the vehicle 10.

[0039] The information processing device 101 determines whether the detected moving object is a suspicious person based on the monitoring result of the moving object output by the monitoring device 100. When it is determined that the detected moving object is a suspicious person, the information processing device 101 outputs warning information to a predetermined output destination.

[0040] (Processing Overview)

[0041] Figure 2 This is a diagram for explaining the outline of processing in one embodiment. Figure 2 Schematic diagram showing the field of view of the EVS provided by the monitoring device 100. In this example, the monitoring device 100 is provided so that the driver's seat, the windshield 211, and the side windows 212 and 213 can be included in the field of view of the EVS from behind the cabin of the vehicle 10.

[0042] EVS detects the brightness change of each pixel and outputs image data representing the brightness change when the brightness change of the pixel exceeds a specified value. The brightness change of the pixel occurs when the subject moves. Therefore, if there is no moving object (hereinafter referred to as a moving object) within the field of view of the EVS, the EVS will not output image data.

[0043] Therefore, it is possible to use the EVS as a surveillance camera to realize power saving of the surveillance system. For example, by setting the information processing device 101 to a power saving state when no monitoring result of a moving object is input, and starting it when the monitoring result of a moving object is input from the surveillance device 100, the power consumption of the information processing device 101 can be reduced even when there is no moving object in the field of view of the EVS.

[0044] However, for example, in the case where the vehicle 10 is parked near a road with heavy traffic, Figure 2 As shown, pedestrians 201 or other vehicles 202 on the road may sometimes enter the field of view of the EVS through the windshield 211. In this case, even if there is no moving object in the cabin of the vehicle 10, the EVS will output the monitoring result of the moving object and the information processing device 101 will start, resulting in a problem that a sufficient power saving effect cannot be obtained.

[0045] In this regard, the monitoring device 100 of this embodiment has, for example, a configuration in which the windshield 211 and the side windows 212 and 213, where the frequency of brightness changes, is set as a non-monitoring area, and an area other than the non-monitoring area is set as a monitoring area. The monitoring device 100 monitors the monitoring area, and when a moving object is detected in the monitoring area, the detection result of the moving object is output to the information processing device 101.

[0046] Thus, when there is no moving object in the cabin of the vehicle 10, the monitoring device 100 will not output the monitoring result of the moving object due to the presence of pedestrians 201 or other vehicles 202 passing on the road, thereby suppressing unnecessary activation of the information processing device 101.

[0047] As described above, according to the present embodiment, a sufficient power saving effect can be obtained in the monitoring system 1 using the EVS as a monitoring camera.

[0048] <Functional structure>

[0049] Figure 3 FIG. 1 is a diagram showing an example of a functional configuration of a monitoring system according to an embodiment. This diagram shows an exemplary functional configuration of a monitoring system 1 in a case where the monitoring device 100 is a monitoring camera.

[0050] (Functional Structure of Monitoring Device)

[0051] exist Figure 3 In the example of , the monitoring device (monitoring camera) 100 has a functional structure including an image acquisition unit 301, an area determination unit 302, a control unit 303, and a monitoring unit 304.

[0052] The image acquisition unit 301 is implemented by, for example, a light receiving element (sensor array) of the EVS, and performs image acquisition processing for acquiring image data representing changes in the intensity of incident light (changes in brightness). For example, the image acquisition unit 301 determines whether the brightness change of the light taken in for each pixel exceeds a specified value, and acquires image data (EVS image data) representing the brightness change of the pixel exceeding the specified value.

[0053] The region determination unit 302 performs region determination processing to determine a monitoring region (first region) to be monitored and a non-monitoring region (second region) not to be monitored in the field of view (field of view of the EVS) of the image acquisition unit 301. For example, the region determination unit 302 sets a region in which the frequency of brightness change is greater than a threshold value as a non-monitoring region (second region) in the image data acquired by the image acquisition unit 301, and sets a region in which the frequency of brightness change is less than the threshold value as a monitoring region (first region).

[0054] The region determination unit 302 may be implemented by a program executed by a computer included in the monitoring device 100 , or may be implemented by hardware included in the monitoring device 100 .

[0055] The control unit 303 performs control processing to control the area in the field of view of the image acquisition unit 301 where the image acquisition unit 301 acquires image data, based on the monitoring area and non-monitoring area determined by the area determination unit 302. The control unit 303 is implemented by hardware configured on the EVS provided in the monitoring device 100, for example.

[0056] Figure 4: is a diagram showing a structural example of an EVS of an embodiment. The EVS 400 of this embodiment, for example, is provided with a mask 420 on a light receiving portion 410 having a sensor array 411. The mask 420 includes, for example, a light shielding portion 421 having a liquid crystal that changes the transmittance of light by applying a voltage, and a control unit 303 that controls the light shielding portion 421. The light shielding portion 421 is arranged to overlap with the sensor array 411 in a plan view, and can reduce the transmittance of light in an arbitrary area 423 of the sensor array 411 (light shielding) according to the control of the control unit 303. In addition, the control unit 303 may be provided on the light receiving portion 410 instead of the mask 420.

[0057] exist Figure 4 In the example, the control unit 303 controls the light shielding unit 421 to reduce the transmittance of light at the position corresponding to the non-monitoring area of ​​the sensor array 411. Thus, the control unit 303 can perform the following control to shield the light received by the light receiving element corresponding to the non-monitoring area in the sensor array 411 to suppress the brightness change, and the conductor in the non-monitoring area is not monitored.

[0058] in addition, Figure 4 The structure of the EVS 400 shown is an example. For example, the control unit 303 can control the area where the image acquisition unit 301 acquires image data through software executed by a computer provided in the monitoring device 100, a signal processing circuit or a DSP (Digital Signal Processor).

[0059] Here, return Figure 3 The functional structure of the monitoring device 100 is further described. The monitoring unit 304 performs monitoring processing to output the monitoring result of the moving object based on the image data acquired by the image acquisition unit 301 in the monitoring area (first area) determined by the area determination unit 302. For example, the monitoring unit 304 monitors the brightness change of the image data acquired by the image acquisition unit 301 in the monitoring area, and outputs the information of the brightness change of the acquired image data as the monitoring result to the information processing device 101. Here, when there is no brightness change in the monitoring area, or when the brightness change is less than the threshold value, the monitoring unit 304 does not output the monitoring result to the information processing device 101. In addition, the monitoring unit 304 may set the threshold value to exclude brightness changes caused by noise, for example.

[0060] (Functional Structure of Information Processing Device)

[0061] The information processing device 101 includes, for example, an image processing unit 311 , an AI (Artificial Intelligence) processing unit 312 , an authentication unit 313 , and an output unit 314 .

[0062] The image processing unit 311 performs image processing such as noise removal on the monitoring result (image showing brightness change) acquired from the monitoring unit 304. The image processing unit 311 is implemented by a program executed by a computer included in the information processing device 101 or a signal processing circuit.

[0063] The AI ​​processing unit 312 determines whether the monitored area (e.g., the interior of the vehicle 10, etc.) is safe in the monitoring results of the image processing performed by the image processing unit 311. If it is determined to be unsafe, the AI ​​processing unit 312 outputs the monitoring results to the authentication unit 313. For example, the AI ​​processing unit 312 uses a plurality of monitoring results and teacher data indicating whether each monitoring result is safe, etc., to input the monitoring results of the image processing performed by the image processing unit 311 into a pre-learned machine learning model to determine whether the monitoring results are safe. For example, when the monitoring results of the image processing performed by the image processing unit 311 include a person, the AI ​​processing unit 312 may determine that the monitoring results are unsafe. The AI ​​processing unit 312 is implemented, for example, by a program executed by a computer included in the information processing device 101.

[0064] The authentication unit 313 compares the monitoring result obtained from the AI ​​processing unit 312 with the authentication information 315 to determine whether the person included in the monitoring result is a legitimate user or a suspicious person. The authentication unit 313 is implemented by a program executed by a computer included in the information processing device 101, for example.

[0065] The output unit 314 outputs a warning message when the authentication unit 313 determines that the person included in the monitoring result is not a legitimate user (when it is determined to be a suspicious person). The output unit 314 is implemented, for example, by a program executed by a computer provided in the information processing device 101. In addition, an example of a specific process performed by the monitoring system 1 according to the warning message will be described later.

[0066] in addition, Figure 3 The functional configuration of the monitoring system 1 described above is an example. For example, the monitoring system 1 may have Figure 5 The functional structure shown.

[0067] Figure 5 FIG. 2 is a diagram showing an example of a functional structure of a monitoring system according to an embodiment. Figure 5 In the example of , the monitoring device 100 includes a monitoring camera 501 and an information processing device (control unit) 101.

[0068] exist Figure 5 In the example, surveillance camera 501 and Figure 3The monitoring device (monitoring camera) 100 described in the above also includes an image acquisition unit 301, an area determination unit 302, a control unit 303, and a monitoring unit 304. Figure 3 Similarly, the information processing device 101 described in FIG. 1 includes an image processing unit 311, an AI processing unit 312, an authentication unit 313, and an output unit 314. As described above, the information processing device 101 can be included in the monitoring device 100 as a control unit of the monitoring device 100.

[0069] <Processing Flow>

[0070] Next, the processing flow of the monitoring method according to the present embodiment will be described.

[0071] [First embodiment]

[0072] (Monitoring Processing)

[0073] Figure 6 is a flowchart showing an example of monitoring processing according to the first embodiment. Figure 3 or Figure 5 An example of monitoring processing executed by the monitoring system 1 having the functional configuration shown.

[0074] In step S601, the region determination unit 302 performs region determination processing, which determines a monitoring region (first region) for monitoring moving objects (or brightness changes) and a non-monitoring region (second region) for not monitoring moving objects in the field of view of the image acquisition unit 301. Figure 2 As described in the above, the areas with high frequency of brightness changes such as the windshield 211 and the side windows 212 and 213 of the vehicle 10 are set as non-monitoring areas, and the areas other than the non-monitoring areas are set as monitoring areas. In addition, an example of the specific processing content of the area determination processing will be described later.

[0075] In step S602, the monitoring device 100 monitors the monitoring area determined by the area determination unit 302. For example, the control unit 303 Figure 4 The shading unit 421 described in the above description is controlled to shading the non-monitoring area determined by the area determination unit 302. As a result, the image acquisition unit 301 acquires image data indicating a change in pixel brightness exceeding a specified value in the monitoring area determined by the area determination unit 302. In addition, the monitoring unit 304 monitors the brightness change of the image data acquired by the image acquisition unit 301 in the monitoring area, and outputs the brightness change information of the acquired image data as a monitoring result (monitoring result of a moving object) to the information processing device 101 when there is a brightness change.

[0076] In step S603, when the information processing device 101 receives the monitoring result from the monitoring unit 304, the information processing device 101 executes the processing after step S604. On the other hand, when the information processing device 101 does not receive the monitoring result from the monitoring unit 304, the monitoring system 1 returns the processing to step S602.

[0077] After moving to step S604, the information processing device 101 executes a suspicious person detection process for detecting a suspicious person based on the monitoring result received from the monitoring unit 304. An example of the specific processing content of the suspicious person detection process will be described later.

[0078] In step S605, if a suspicious person is detected in the suspicious person detection process, the information processing device 101 moves the process to step S606. On the other hand, if a suspicious person is not detected in the suspicious person detection process, the information processing device 101 moves the process to step S607.

[0079] After moving to step S606, the output unit 314 outputs the warning information to a predetermined output destination.

[0080] In step S607, the monitoring system 1 determines whether to terminate the monitoring process. For example, the monitoring system 1 may determine that the monitoring process is terminated when the ignition power of the vehicle 10 is turned on. When the monitoring process is terminated, the monitoring system 1 terminates. Figure 6 On the other hand, if the monitoring process is not ended, the monitoring system 1 returns the process to step S602.

[0081] pass Figure 6 By the processing, the monitoring system 1 can suppress unnecessary activation of the information processing device 101 when there is no brightness change in the monitoring area determined in step S601 (when there is no moving object in the cabin of the vehicle 10).

[0082] in addition, Figure 6 The monitoring process shown is an example. For example, when a predetermined time has passed after the monitoring device 100 executes the area determination process of step S601, it may execute the area determination process again to update the monitoring area and the non-monitoring area.

[0083] (Region determination processing)

[0084] Figure 7 is a flowchart showing an example of the area determination process of the first embodiment. Figure 6 This is an example of the area determination processing performed by the area determination unit 302 in step S601.

[0085] In step S701, the area determination unit 302 acquires image data of a predetermined period from the image acquisition unit 301 in a state where no non-monitoring area is set. Here, the "predetermined period" may be a predetermined fixed value (e.g., several seconds to several minutes), or may be dynamically determined by the area determination unit 302 according to the presence or absence of brightness changes, etc.

[0086] In step S702, the region determination unit 302 calculates the frequency of brightness change in each region based on the acquired image data. Here, the "region" may be, for example, a region determined by the region determination unit 302 to include pixels whose brightness change is greater than a predetermined value, or a grid-like region of a predetermined size.

[0087] In step S703, the region determination unit 302 determines whether there is a region whose frequency of brightness change is greater than or equal to a threshold value. If there is a region whose frequency is greater than or equal to the threshold value, the region determination unit 302 moves the process to step S704. On the other hand, if there is no region whose frequency is greater than or equal to the threshold value, the region determination unit 302 ends the process. Figure 7 processing.

[0088] After moving to step S704, the region determination unit 302 sets the region where the frequency of brightness change is greater than or equal to the threshold as the non-monitoring region. In addition, in the field of view of the image acquisition unit 301, the region other than the non-monitoring region becomes the monitoring region.

[0089] (Detection and processing of suspicious persons)

[0090] Figure 8 is a flowchart showing an example of a suspicious person detection process according to the first embodiment. Figure 6 This is an example of suspicious person detection processing performed by the information processing device 101 in step S604.

[0091] In step S801 , the image processing unit 311 performs image processing such as noise removal based on the monitoring result (image showing brightness change) acquired from the monitoring unit 304 .

[0092] In steps S802 and S803, the AI ​​processing unit 312 determines whether the monitored area (e.g., the interior of the vehicle 10) is safe based on the monitoring results of the image processing performed by the image processing unit 311. For example, the AI ​​processing unit 312 inputs the monitoring results to a machine learning model that has been pre-learned to predict whether the interior of the vehicle is safe, and determines whether it is safe. When it is determined to be safe, the information processing device 101 moves the processing to step S804. On the other hand, when it is determined to be unsafe, the information processing device 101 moves the processing to step S805.

[0093] After moving to step S804, the information processing device 101 determines that no suspicious person is detected.

[0094] On the other hand, after moving to step S805, the authentication unit 313 performs authentication processing to compare the acquired monitoring result with the authentication information 315 to determine whether the person included in the monitoring result is a legitimate user.

[0095] In step S806, when the person included in the monitoring result is a legitimate user, the information processing device moves the process to step S804. On the other hand, when the person included in the monitoring result is not a legitimate user, the information processing device moves the process to step S807.

[0096] When the process moves to step S807 , the information processing device 101 determines that a suspicious person has been detected.

[0097] also, Figure 8 The processing is an example of suspicious person detection processing performed by the information processing device 101. For example, the processing of step S801 can be performed by the monitoring unit 304 or the AI ​​processing unit 312, etc., or can be omitted. In addition, in step S805, the authentication unit 313 can also request biometric authentication or password authentication from the person in the vehicle 10 to authenticate whether the person in the vehicle is a legitimate user, in place of (or in addition to) the acquired monitoring result. In addition, the authentication processing of step S805 can also be omitted.

[0098] As described above, according to the first embodiment, by setting a non-monitoring area in the monitoring system 1 using the EVS as a monitoring camera, the output of unnecessary monitoring nodes is suppressed, thereby reducing the power consumption of the information processing device 101.

[0099] [Second embodiment]

[0100] Fig. 9 This is a diagram for explaining the area change process according to the second embodiment. Fig. 9 FIG. 910 on the upper side shows a schematic diagram of the field of view of the image acquisition unit 301. In addition, in FIG. 910, as shown in FIG. Figure 2 As described above, non-monitoring areas 911 , 912 , and 913 are set on the windshield and left and right side windows of the vehicle 10 .

[0101] In this state, it is assumed that a moving object (e.g., a suspicious person, etc.) 901 is detected in a monitoring area other than the non-monitoring areas 911, 912, and 913. In this case, the monitoring device 100, such as Fig. 9 As shown in FIG. 920 on the lower side, the non-monitoring area (second area) near the moving object 901 is changed to the monitoring area (first area).

[0102] For example, in the example of FIG920, the monitoring device 100 changes the non-monitoring area near the moving object 901 into a monitoring area by reducing the non-monitoring area 911 of FIG910 to the non-monitoring area 921 of FIG920. However, the present invention is not limited thereto, and the monitoring device 100 may change the non-monitoring area near the moving object 901 into a monitoring area by changing the non-monitoring area 911 of FIG910 into a monitoring area. Alternatively, the monitoring device 100 may also change the non-monitoring area near the movable object 901 into a monitoring area by using the non-monitoring areas 911, 912, and 913 of FIG910 as non-monitoring areas.

[0103] In addition, the moving objects monitored by the monitoring system 1 are not limited to suspicious persons or objects in the vehicle interior, and may be, for example, doors of the vehicle 10. For example, the monitoring device 100 may change the non-monitored area (for example, the non-monitored area 912) near the right door of the vehicle 10 to the monitored area when the right door of the vehicle 10 is opened or closed.

[0104] <Processing Flow>

[0105] Fig.10 is a flowchart showing an example of the area change process of the second embodiment. Figure 6 The monitoring process of the first embodiment described in the embodiment is repeatedly executed in parallel Fig.10 processing.

[0106] In step S1001, the region determination unit 302 determines whether a moving object is detected in the monitoring area based on the image data acquired by the image acquisition unit 301. If a moving object is not detected in the monitoring area, the region determination unit 302 ends (or re-executes) the process. Fig.10 On the other hand, when a moving object is detected in the monitoring area, the area determination unit 302 moves the process to step S1002.

[0107] In step S1002, the region determination unit 302 changes the non-monitoring region (second region) near the detected moving object to the monitoring region (first region). Fig. 9 As described above, the non-monitoring area 911 near the detected moving object 901 is reduced to be the non-monitoring area 921. However, the present invention is not limited thereto. Fig. 9 As monitoring areas, all non-monitoring areas 911 of the moving object 901 detected in step S1002 are used as monitoring areas. Alternatively, the area determination unit 302 may also use all non-monitoring areas 911, 912, and 913 as monitoring areas. As described above, the area determination unit 302 only needs to change the non-monitoring area near at least the detected moving object into the monitoring area in step S1002.

[0108] According to the second embodiment, the monitoring system 1 can facilitate the monitoring of a moving object and can improve the monitoring accuracy of the moving object.

[0109] [Third Embodiment]

[0110] In the third embodiment, an example of using the warning information output by the information processing device 101 will be described.

[0111] Fig.11 FIG. 1 is a diagram showing an example of a system configuration of a monitoring system according to a third embodiment. Fig.11 In the example of , the vehicle 10 includes a communication unit 1101 and a vehicle invalidation unit 1102 in addition to the monitoring device 100 and the information processing device 101. Here, the monitoring device 100 and the information processing device 101 are, for example, the monitoring device 100 and the information processing device 101 of the first embodiment or the second embodiment.

[0112] The communication unit 1101 is implemented by, for example, an electronic control unit (ECU) of the vehicle 10 and a wireless communication module that connects the vehicle 10 to the communication network N. When the communication unit 1101 receives warning information from the information processing device 101, it notifies the owner of the vehicle 10 or a predetermined notification target such as a security company through the external server 1110 that there is a moving object (suspicious person, etc.) in the vehicle 10.

[0113] Thus, the monitoring system 1 of the third embodiment can promptly notify a predetermined notification target that the vehicle 10 is at risk of being stolen. In addition, the information processing device 101 may include a function of the communication unit 1101 .

[0114] The vehicle disabling unit 1102 is implemented by, for example, an electronic control device of the vehicle 10, and disables (sets to an inoperative state) the vehicle 10 when receiving a warning message from the information processing device 101. For example, the vehicle disabling unit 1102 may disable the engine of the vehicle 10 through software processing, or may destroy a part of the components of the vehicle 10 (for example, disconnecting a fuse or an e-fuse in a semiconductor chip, etc.).

[0115] Thus, since the vehicle 10 is in an inoperative state, even if the vehicle 10 is stolen, its economic value when it is sold is reduced, thereby reducing the motivation for vehicle theft. In addition, the owner (legitimate user) of the vehicle 10 can restore the vehicle 10 to an operational state by taking the invalidated vehicle 10 to a regular dealer, etc., replacing damaged parts, or performing a batch processing of software, etc.

[0116] As described above, the information processing device 101 controls the disabling of the vehicle 10 based on the monitoring result of the moving object in the vehicle cabin by using the vehicle disabling unit 1102. In addition, the information processing device 101 may have the function of the vehicle disabling unit 1102.

[0117] In addition, the vehicle 10 may include either the communication unit 1101 or the vehicle invalidation unit 1102. In addition, the vehicle 10 is preferably configured such that whether or not to validate the function of the vehicle invalidation unit 1102 can be set by the user.

[0118] <Example of use case>

[0119] In the first to third embodiments, the monitoring system 1 is described assuming that a suspicious person enters the vehicle 10. However, the monitoring system 1 is not limited to this, and can be applied to various other uses.

[0120] For example, the monitoring system 1 can also be applied to monitoring purposes such as notifying a driver who locked the vehicle 10 or a security company or other specified notification target that there are passengers stranded in the vehicle 10 when a moving object is detected in the vehicle 10 after the vehicle 10 is locked.

[0121] In addition, the present embodiment is not limited to the vehicle 10 , and can also be applied to, for example, a surveillance camera installed indoors or outdoors.

[0122] Fig.12 1 is a diagram showing an example of a use scenario of a monitoring system according to an embodiment. For example, the monitoring system 1 may be a device that installs a monitoring device 100 including a monitoring camera 501 and an information processing device 101 indoors to monitor a dynamic object (eg, a suspicious person) indoors.

[0123] FIG1200 is a schematic diagram showing the field of view of the image acquisition unit 301 (or EVS) of the monitoring device 100. In this example, the monitoring device 100 is installed indoors, and is installed so that the indoor area including the window 1201 is within the field of view of the image acquisition unit 301.

[0124] In this case, the monitoring device 100 can monitor dynamic objects in the room (for example, intrusion of a suspicious person, etc.) while suppressing the power consumption of the information processing device 101 by setting the window 1201 with outdoor activities that are not the monitoring object as the non-monitoring area 1202. In addition, the monitoring device 100 is not limited to the window 1201. For example, the screen of a TV set in the room, a tank for ornamental fish, or a cage for a pet, etc., where there are activities, can be set as a non-monitoring area.

[0125] <Hardware Structure>

[0126] Figure 3The information processing device 101 and Figure 5 The monitoring device 100 has, for example, Fig.13 The hardware structure of the computer 1300 is shown.

[0127] Fig.13 The computer 1300 includes, for example, a processor 1301 , a memory 1302 , a storage device 1303 , an I / F (Interface) 1304 , an input device 1305 , an output device 1306 , a communication device 1307 , and a bus 1308 .

[0128] The processor 1301 is, for example, a computing device such as a CPU (Central Processing Unit) that executes a predetermined process by executing a program stored in a storage medium such as a storage device 1303. The memory 1302 includes, for example, a volatile memory RAM (Random Access Memory) used as a work area of ​​the processor 1301, and a non-volatile memory ROM (Read Only Memory) that stores a program for starting the processor 1301. The storage device 1303 is, for example, a large-capacity non-volatile storage device such as an SSD (Solid State Drive) or an HDD (Hard Disk Drive). The I / F 1304 includes various interfaces for connecting external devices to the computer 1300.

[0129] The input device 1305 includes various devices for receiving input from the outside (e.g., keyboard, touch pad, pointing device, microphone, switch, button or sensor). The output device 1306 includes various devices for performing output to the outside (e.g., display, speaker, indicator, etc.). The communication device 1307 includes various communication devices for communicating with other devices through a wired or wireless network. The bus 1308 is connected to the above-mentioned structural elements, for example, to transmit address signals, data signals and various control signals.

[0130] As described above, according to the embodiments of the present invention, a sufficient power saving effect can be obtained in a monitoring system using an EVS as a monitoring camera.

[0131] As mentioned above, although embodiment of this invention was described, this invention is not limited to this specific embodiment, Various deformation|transformation and change are possible within the range of the summary of this invention described in a claim.

[0132] Explanation of symbols

[0133] 1. Monitoring system

[0134] 10 Vehicles

[0135] 100 surveillance devices

[0136] 101 Information Processing Device

[0137] 301 Image Acquisition Department

[0138] 302 Regional Determination Department

[0139] 303 Control Department

[0140] 304 Monitoring Department

[0141] 1101 Communications Department

[0142] 1102 Vehicle Invalidation Department

Claims

1. A monitoring device, comprising: an image acquisition unit that acquires image data representing changes in the intensity of incident light; an area determination unit that determines a first area to be monitored and a second area not to be monitored in the field of view of the image acquisition unit; and The monitoring unit outputs a monitoring result of the moving object based on the image data acquired by the image acquisition unit in the first area.

2. The monitoring device according to claim 1, wherein: The change in the intensity of the light includes a change in brightness, The region determination unit sets a region in which the frequency of the change in the brightness in the image data acquired by the image acquisition unit is equal to or greater than a threshold value as the second region.

3. The monitoring device according to claim 1 or 2, further comprising: a shading unit for shading a specified area in the field of view of the image acquisition unit; and The control unit controls the predetermined area so as to shield the second area from light in the field of view of the image acquisition unit.

4. The monitoring device according to claim 1 or 2, wherein: When the monitoring unit detects a moving object in the first area, The region determination unit changes the second region near the moving object to the first region.

5. A monitoring system, comprising the monitoring device and the information processing device according to claim 1, wherein: The monitoring device outputs the monitoring result of the moving object to the information processing device.

6. The monitoring system according to claim 5, wherein: The information processing device outputs predetermined warning information based on the detection result of the moving object.

7. The monitoring system according to claim 5 or 6, wherein: The monitoring device is a monitoring camera mounted on a vehicle. The information processing device controls the invalidation of the vehicle according to the monitoring result of the moving object.

8. The monitoring system according to claim 7, wherein: The information processing device is an electronic control device included in the vehicle.

9. A monitoring system, comprising: an image acquisition unit that acquires image data representing changes in the intensity of incident light; an area determination unit that determines a first area to be monitored and a second area not to be monitored in the field of view of the image acquisition unit; and The monitoring unit outputs a monitoring result of the moving object based on the image data acquired by the image acquisition unit in the first area.

10. A monitoring method, configured to cause a monitoring device to execute: An image acquisition process of acquiring image data representing changes in the intensity of incident light; an area determination process of determining a first area to be monitored and a second area not to be monitored in a field of view of the image acquisition process; and The monitoring process outputs a monitoring result of the moving object based on the image data acquired in the first area by the image acquisition process.

Images