JP5499752B2 - Camera state monitoring apparatus, camera state monitoring program, and camera state monitoring method - Google Patents

Description

  This case relates to a camera state monitoring apparatus, a camera state monitoring program, and a camera state monitoring method.

  Conventionally, as a method for determining whether a camera such as a monitoring camera is operating normally, there are methods as described in Patent Documents 1 to 3. The method of Patent Document 1 determines that the monitoring camera is abnormal when there is no change in the file size within a certain period of time. The method of Patent Document 2 is to determine that the camera is in an abnormal operation state when the same state of sampling images continues. Further, the method of Patent Document 3 calculates the data size of a compressed image at regular intervals and searches for a frame in which the image size changes rapidly.

JP 2005-117339 A JP 2001-54100 A JP 2001-57675 A

  However, Patent Documents 1 to 3 do not consider the case where the scenery changes suddenly due to changes in the weather. For this reason, even if it is determined that the camera is operating abnormally, it may not be possible to determine whether the reason is a change in weather or a camera failure.

  Accordingly, the present invention has been made in view of the above problems, and an object thereof is to provide a camera state monitoring device, a camera state monitoring program, and a camera state monitoring method that can determine a camera abnormality with high accuracy. .

  The camera state monitoring device described in this specification calculates the amount of data when the video data captured by one of the plurality of cameras is compressed, and was previously captured by the one camera. A first rate-of-change calculating unit that calculates a rate of change from the amount of data when the video data is compressed, and the one of the plurality of cameras that is located within a predetermined distance from the one camera and is captured by the one camera A camera extraction unit that extracts a camera that captures a predetermined angle range with respect to a direction to be calculated; and a data amount when the video data captured by the camera extracted by the camera extraction unit is compressed, and is extracted A second rate-of-change calculator that calculates a rate of change from the amount of data when video data previously captured by the camera is compressed, and a rate of change calculated by the first rate-of-change calculator By comparing the rate of change calculated by the second change rate calculating section, and a, and an abnormality determination unit determining abnormality of the one camera.

  The camera status monitoring program described in this specification calculates the amount of data when a computer compresses video data captured by one of a plurality of cameras, and the previous one is captured by the one camera. A first rate-of-change calculating unit that calculates a rate of change from a data amount when compressed video data is compressed, and is present within a predetermined distance from the one camera among the plurality of cameras, and of the one camera A camera extraction unit that extracts a camera that captures a predetermined angle range based on a direction to shoot, calculates a data amount when video data captured by the camera extracted by the camera extraction unit is compressed, and is extracted A second rate-of-change calculator that calculates a rate of change from the amount of data when video data previously captured by the camera is compressed, and the first rate-of-change calculator And issued rate of change, the by comparing the calculated rate of change by the second change rate calculating section, and an abnormality determination unit determining abnormality of the one camera, is to function.

  The camera state monitoring method described in this specification calculates the amount of data when video data shot by one of a plurality of cameras is compressed, and the video shot before that by the one camera. A first rate-of-change calculating step for calculating a rate of change from the amount of data when the data is compressed, and the one of the plurality of cameras that is within a predetermined distance from the one camera and is photographed by the one camera A camera extraction step for extracting a camera that captures a predetermined angle range based on a direction, and a data amount when the video data captured by the camera extracted in the camera extraction step is compressed, and the extracted A second rate-of-change calculating step for calculating a rate of change from a data amount when video data previously captured by the camera is compressed; A change ratio calculated in step, and compares the calculated change rate in the second change rate calculating step includes the abnormality determining step of determining an abnormality of the one camera.

  The camera state monitoring device, the camera state monitoring program, and the camera state monitoring method described in the present specification have an effect that a camera abnormality can be determined with high accuracy.

It is a block diagram which shows the surveillance camera system containing the camera state monitoring apparatus which concerns on one Embodiment. It is a figure which shows an example of arrangement | positioning of the monitoring camera. It is a block diagram which shows the structure of a surveillance camera. It is a block diagram which shows the structure of a database, and the database utilization condition in a camera abnormality determination part and a state estimation part. It is a figure which shows camera metadata DB. It is a figure which shows still image log | history DB. It is a figure which shows abnormality determination threshold value DB. It is a figure which shows abnormal camera DB. It is a flowchart which shows the process in a camera abnormality determination part. It is a figure which shows the subroutine of step S20 of FIG. It is a figure which shows the subroutine of step S30 of FIG. It is a figure which shows the subroutine of step S40 of FIG. It is a figure which shows the subroutine of step S50 of FIG. It is a figure which shows the subroutine of step S60 of FIG. It is a figure which shows the subroutine of step S90 of FIG. It is a flowchart which shows the process performed in a state estimation part. It is a figure for demonstrating the calculation method of an imaging direction. It is a figure which shows an example of the window displayed on a user terminal.

Hereinafter, an embodiment of a camera state monitoring device will be described in detail with reference to FIGS. FIG. 1 is a block diagram showing a surveillance camera system (CCTV (Closed-circuit Television) camera system) 100 including a camera state monitoring device 10. As shown in FIG. 1, a surveillance camera system 100 includes a plurality of surveillance cameras C ₁ -C _n, these surveillance cameras C ₁ -C _n to connected IP encoder E ₁ to E _n, camera status monitoring device 10, A camera control device 12 and a user terminal 14 are provided. The IP encoders E _{1 to} E _n , the camera state monitoring device 10, the camera control device 12, and the user terminal 14 are connected to the IP network 16.

The monitoring cameras C _{1 to} C _n are arranged at predetermined arrangement intervals in the vicinity of a road 90 such as an expressway as shown in FIG. As this arrangement interval, for example, an interval of 200 m can be adopted. In this case, about five surveillance cameras are arranged between kiloposts. In FIG. 3, the monitoring cameras C _{1 to} C _n are shown in a block diagram. As shown in FIG. 3, the monitoring cameras C _{1 to} C _n detect the shooting unit 2, the swing unit 4 that changes the shooting direction of the shooting unit 2, and the swing angle of the swing unit 4. And a pulse detector 6 for detecting a pulse. The head swing unit 4 can change the shooting direction (shooting direction) between, for example, right 175 ° (+ 175 °) and left 175 ° (−175 °). The pulse detector 6 includes an incremental rotary encoder that outputs a quadrature two-phase pulse, and detects a pulse as an output from the rotary encoder. For example, when 1 ° is 417 pulses in a camera that can swing between 175 ° to the left and 175 ° to the right, the number of pulses in the range of −72975 pulses to +72975 pulses is detected.

Returning to FIG. 1, the IP encoders E _{1 to} E _n capture images input from the imaging units 2 of the monitoring cameras C _{1 to} C _n . Further, the IP encoders E _{1 to} E _n transmit streaming to the IP network in real time with designated parameters (encoding, beatlet, etc.), and perform live distribution to the user terminal 14.

  The camera state monitoring apparatus 10 includes a camera abnormality determination unit 20, a state estimation unit 30, and a database 40. In the present embodiment, the functions of the camera abnormality determination unit 20 and the state estimation unit 30 are realized by a program built in the computer system of the camera state monitoring apparatus 10. However, the present invention is not limited to this, and each unit may be configured by an actual device.

The camera abnormality determination unit 20 includes a first change rate calculation unit 22, a camera extraction unit 24, a second change rate calculation unit 26, an abnormality determination unit 28, and a control unit 29 that performs overall control of these units. . The first rate-of-change calculator 22 calculates the amount of data when video data (still images) taken by one of the plurality of monitoring cameras C _{1 to} C _n (referred to as a specific camera) is compressed. To do. Further, the first change rate calculation unit 22 calculates a change rate from the data amount when video data (still image) taken before (for example, most recently) by the specific camera is compressed. The camera extraction unit 24 extracts a monitoring camera that is present within a predetermined distance from the specific camera and that captures a predetermined angle range based on a direction captured by the specific camera.

  The second change rate calculation unit 26 calculates the data amount when the video data taken by the monitoring camera extracted by the camera extraction unit 24 is compressed. In addition, the second change rate calculation unit 26 calculates a change rate from the data amount when video data captured before (for example, the latest) by the extracted monitoring camera is compressed. When the camera extraction unit 24 extracts a plurality of monitoring cameras, the second change rate calculation unit 26 calculates a change rate for each extracted monitoring camera and calculates an average value of the change rates.

  The abnormality determination unit 28 compares the change rate calculated by the first change rate calculation unit 22 with the change rate calculated by the second change rate calculation unit 26 (or an average value of the change rates), and determines the specific camera. It is determined whether or not is abnormal.

The state estimation unit 30 estimates whether or not each of the plurality of monitoring cameras C _{1 to} C _n is actually abnormal. The state estimation unit 30 is configured based on a control state indicating whether each monitoring camera is controlled by a user or the like and a browsing state indicating whether each monitoring camera is viewed by a user or the like. It is estimated whether the monitoring camera is abnormal.

FIG. 4 is a block diagram illustrating the configuration of the database 40 and the database usage status in the camera abnormality determination unit 20 and the state estimation unit 30. As shown in FIG. 4, the database 40 includes a camera metadata DB 42, a still image history DB 44, an abnormality determination threshold DB 46, and an abnormal camera DB 48. The camera metadata DB 42 has items as shown in FIG. Specifically, the camera metadata DB 42 includes a camera ID item, a camera name item, a latitude and longitude item, a multicast address item, a port number item, and a reference coordinate item. In FIG. 5, “00001”, “00002”, “00003”... Are employed as camera IDs of the monitoring cameras C ₁ , C ₂ , C ₃ . As camera names of the monitoring cameras C ₁ , C ₂ , C ₃ ..., “Camera 00001”, “Camera 00002”, “Camera 00003”. The item of reference coordinates indicates coordinates (reference coordinates) in a direction in which the surveillance camera is not swinging, that is, in a direction in which the swing angle is 0 °.

The still image history DB 44 has items as shown in FIG. Specifically, the still image history DB 44 has a camera ID item, a capture date / time item, a still image size item, a difference value item from the previous time, and a change rate item. In FIG. 6, only the still image history DB of the monitoring camera with the camera ID “00001” (the monitoring camera C _{1 in} FIG. ₁ ) is shown, but the same applies to the other monitoring cameras C _{2 to} C _n. Still image history DB exists (not shown). The still image size item in FIG. 6 stores the data amount when the first change rate calculation unit 22 and the second change rate calculation unit 26 compress the video data (still image) taken by the monitoring camera. The In the item of difference value from the previous time, the difference value of the still image size stored in the adjacent rows in the upper and lower parts of FIG. 6 is stored. In the change rate item, the change rate represented by the following equation (1) is stored.
Rate of change (%) = difference value / previous value × 100 (1)

As shown in FIG. 7, the abnormality determination threshold DB 46 includes a camera ID item and a threshold η item. In the abnormality determination threshold value DB 46, a threshold value η that is used when the abnormality determination unit 28 determines an abnormality of the monitoring cameras C _{1 to} C _n is set for each monitoring camera. The threshold value η is a value updated by the state estimation unit 30 as described later.

  As shown in FIG. 8, the abnormal camera DB 48 includes a camera ID item, a camera name item, and an abnormality detection date / time item. In the abnormal camera DB 48, the camera ID, name, and abnormality detection date and time of the monitoring camera determined to be abnormal by the abnormality determination unit 28 are added. In addition, the monitoring camera data (camera ID, name, and abnormality detection date and time) estimated by the state estimation unit 30 to be normal are deleted from the abnormal camera DB 48.

Returning to FIG. 1, when the camera control device 12 receives an instruction (control information or the like) from the user terminal 14, content such as video data acquired via the monitoring cameras C _{1 to} C _n according to the instruction. Is delivered to the user terminal 14. For example, when an instruction is issued from the user terminal 14 to display the video of a certain monitoring camera on the screen, the camera control device 12 displays the video data acquired from the monitoring camera on the screen of the user terminal 14. Display above. When the user terminal 14 gives an instruction to change the shooting angle of a certain monitoring camera, the camera control device 12 controls the swing unit 4 of the specific monitoring camera to perform shooting. The shooting direction of the unit 2 is changed.

  Furthermore, the camera control device 12 transmits information indicating a control state indicating whether a certain monitoring camera is controlled by the user or the like to the state estimation unit 30 at the user terminal 14. Similarly, the camera control device 12 transmits information indicating a browsing state indicating whether a certain monitoring camera is being browsed by a user or the like to the state estimation unit 30.

  The user terminal 14 includes a PC (Personal Computer) and the like. A plurality of user terminals 14 may be connected to the IP network 16.

  Next, processing of the camera state monitoring apparatus 10 according to the present embodiment will be described along the flowcharts of FIGS. 9 to 16 with reference to other drawings as appropriate. FIG. 9 is a flowchart showing processing in the camera abnormality determination unit 20. As shown in FIG. 9, in the camera state monitoring apparatus 10, first, the control unit 29 sets m to 1 (step S10). Next, the first rate-of-change calculating unit 22 executes a process of capturing a compressed still image of the m-th (here, the first) camera (step S20). Next, the first change rate calculation unit 22 executes a step of calculating a difference value between the compressed image size and the previous size (step S30). Next, the camera extraction unit 24 executes a process of extracting a monitoring camera to be compared based on the shooting direction of the m-th monitoring camera (step S40). Next, the second change rate calculation unit 26 executes a step of calculating the average value of the change rates of the monitoring cameras extracted in step S40 (step S50). Next, the abnormality determination unit 28 executes a step of determining an abnormality of the m-th monitoring camera based on the calculation results of step S30 and step S50 (step S60). Next, the control unit 29 determines whether m is n (n is the total number of a plurality of monitoring cameras) (step S70). If the determination is negative, m is incremented by one. (M ← m + 1) is performed (step S80). Thereafter, by repeating step S20 to step S80 until the determination in step S70 is affirmed, abnormality determination is performed for the second, third,. Then, when the determination in step S70 is affirmed, the control unit 29 executes an abnormal camera information providing step of providing information on the abnormal camera to the user terminal 14 via the IP network 16 (step S90). Thereafter, step S10 to step S90 are sequentially repeated.

Next, each process (subroutine) will be described with reference to the flowcharts of FIGS. FIG. 10 shows the subroutine of step S20 of FIG. As shown in FIG. 10, the first change rate calculation unit 22 acquires the multicast address and the port number of the m-th monitoring camera C _m from the camera metadata DB 42 in step S202 ((1 in FIG. 4). )). Then, the first change rate calculating section 22, in step S204, a multicast address acquired, requesting a port number to the IP network side receives the video data from the monitoring camera C _m. Next, in step S206, the first change rate calculation unit 22 creates a compressed still image from the video data, and registers the still image size (compressed image size) in the still image history DB 44 ((2) in FIG. 4). . Thereafter, the process proceeds to step S30 in FIG.

  FIG. 11 shows the subroutine of step S30 of FIG. As shown in FIG. 11, in step S302, the first change rate calculation unit 22 reads the previous value and the current value of the compressed image size from the still image history DB 44 ((3) in FIG. 4), and compresses the compressed image size. The difference value between the previous value and the current value is calculated. Next, in step S304, the first change rate calculation unit 22 registers the difference value calculated in step S302 in the still image history DB 44 ((2) in FIG. 4). Next, in step S306, the first change rate calculation unit 22 calculates the change rate S from Equation (1) described above using the difference value and the previous value. Next, in step S308, the first change rate calculation unit 22 registers the change rate S in the still image history DB 44 ((2) in FIG. 4). Thereafter, the process proceeds to step S40 in FIG.

FIG. 12 shows the subroutine of step S40 in FIG. As shown in FIG. 12, the camera extraction unit 24 first issues a camera state acquisition command of the mth (here, the first) surveillance camera in step S402 to acquire the camera state. Here, the camera state includes the number of pulses detected by the pulse detector 6. Next, in step S404, the camera extraction unit 24 determines to calculate the swing angle θ of the swing unit 4 based on the number of pulses. In this case, as described above, when 1 ° is represented by 417 pulses, the swing angle θ can be calculated from the following equation (2).
Swing angle θ = (number of pulses / 417) × (π / 180) (2)

  Next, in step S <b> 406, the camera extraction unit 24 acquires the reference coordinates of the mth camera from the camera metadata DB 42. Next, in step S408, the camera extraction unit 24 calculates the actual shooting direction α from the reference coordinates and the angle θ. Specifically, the camera extraction unit 24 uses the reference coordinates shown in FIG. 17 and the coordinates (latitude and longitude) of the mth monitoring camera stored in the camera metadata DB 42 as the reference for the mth monitoring camera. Specify the direction when facing the direction of coordinates. Then, the actual shooting direction α is calculated from the swing angle θ calculated in step S404.

Returning to FIG. 12, in the next step S410, the camera extracting unit 24 selects a monitoring camera located within a predetermined distance (for example, within a radius of 1 km) from the m-th monitoring camera based on the latitude and longitude of the camera metadata DB. It is specified ((4) in FIG. 4). For example, if the m-th monitoring camera is the monitoring camera C ₄ in the arrangement of the monitoring cameras as shown in FIG. 2, the monitoring cameras specified in step S410 are the monitoring cameras C ₂ , C ₃ , C ₅ , C _6, the C _7. It is assumed that the number of surveillance cameras identified in step S410 is p.

  Next, the camera extraction unit 24 sets the parameter k to 1 in step S412. Next, in step S414, the camera extraction unit 24 selects a camera with a camera ID that is kth smallest (here, the first) among the p surveillance cameras identified in step S410.

  Next, in step S416, the camera extraction unit 24 issues a camera state acquisition command for the monitoring camera selected in step S414, and acquires the camera state. This process is the same as step S402 described above. Next, in step S418, the swing angle ψ of the surveillance camera selected from the camera state (number of pulses) is calculated. This process is the same as step S404 described above. Next, in step S420, the reference coordinates of the selected surveillance camera are acquired from the camera metadata DB. This process is the same as step S406 described above. In step S422, the actual shooting direction β is calculated from the reference coordinates and the angle ψ. This process is the same as step S408 described above.

  Next, in step S424, the camera extraction unit 24 calculates a difference (absolute value) between the shooting direction α calculated in step S408 and the shooting direction β calculated in step S422. Then, the camera extraction unit 24 determines whether or not the absolute value of the difference between α and β is smaller than a predetermined threshold γ (where γ is a value such that the difference between α and β can be regarded as 0). . The case where the determination is affirmed is a case where the shooting direction of the m-th monitoring camera and the shooting direction of the selected monitoring camera are substantially the same.

  If the determination in step S424 is affirmed, in step S426, the camera extraction unit 24 extracts the selected camera, and the process proceeds to step S428. On the other hand, if the determination in step S424 is negative, the process proceeds to step S428 without passing through step S426.

  Next, the camera extraction unit 24 determines whether or not k is smaller than p in step S428 described above. If the determination here is affirmative, k is incremented by 1 (k ← k + 1) in step S430, and the process returns to step S414. Then, by repeating steps S414 to S430, all of the surveillance cameras that are located within a radius of 1 km and have photographed substantially the same direction are extracted. Thereafter, when the determination in step S428 is negative, the process proceeds to step S50 in FIG.

  FIG. 13 shows the subroutine of step S50 of FIG. The processing of FIG. 13 is the shooting data of the monitoring camera extracted in the processing of FIG. 12 (the monitoring camera that is located within a radius of 1 km from the m-th monitoring camera and has taken the same direction as the m-th monitoring camera). The average value of the rate of change is calculated.

  Specifically, as illustrated in FIG. 13, first, the second change rate calculation unit 26 acquires the multicast addresses and port numbers of all the extracted surveillance cameras from the camera metadata DB 42 in step S502. ((5) in FIG. 4).

  Next, in step S504, the second change rate calculation unit 26 requests the acquired multicast address and port number from the IP network side, and receives video data from each extracted surveillance camera. Next, in step S506, the second change rate calculation unit 26 creates a compressed still image from the video data, and registers the compressed image size in the still image history DB 44 ((6) in FIG. 4). Next, in step S508, the second change rate calculation unit 26 reads the previous value and current value of the compressed image size from the still image history DB 44 ((7) in FIG. 4), and the previous value and current value of the compressed image size. The difference value is calculated. Next, in step S510, the second change rate calculation unit 26 registers the difference value calculated in step S508 in the still image history DB 44 ((6) in FIG. 4). Next, in step S512, the second change rate calculation unit 26 calculates the change rate T from Equation (1) described above using the difference value and the previous value. Next, in step S514, the second change rate calculation unit 26 registers the change rate T in the still image history DB 44 ((6) in FIG. 4). Furthermore, after calculating the average value T ′ of the extracted change rates T of the respective monitoring cameras, the second change rate calculation unit 26 proceeds to step S60 of FIG.

  In the above description, the case where the average value T ′ of the change rates T of the plurality of cameras is calculated on the assumption that a plurality of cameras are extracted in the processing of FIG. 12 is described, but the present invention is not limited to this. is not. For example, in the processing of FIG. 12, only one camera may be extracted. In such a case, in step S516, the extracted change rate T of the camera may be replaced with the average value T '.

  FIG. 14 shows the subroutine of step S60 of FIG. As shown in FIG. 14, in step S602, the abnormality determination unit 28 calculates an absolute value of S-T ′. Next, in step S604, the abnormality determination unit 28 determines whether or not the absolute value of S-T ′ is greater than the abnormality determination threshold η. Here, the threshold η is set for each surveillance camera as shown in FIG. Therefore, the abnormality determination unit 28 reads the threshold value η set for the m-th (here, the first) monitoring camera from the abnormality determination threshold value DB 46 ((8) in FIG. 4), and the threshold value η and ST ′ Compare the absolute value of.

  If the determination in step S604 is affirmed, it can be determined that the m-th monitoring camera is abnormal. Therefore, in step S606, the abnormality determination unit 28 registers the m-th monitoring camera in the abnormal camera DB 48 (FIG. 4 (9)). Then, the process proceeds to step S70 in FIG. On the other hand, if the determination in step S604 is negative, the process proceeds to step S70 in FIG.

As described above, when the processes of steps S20 to S60 are repeatedly performed while incrementing m, only the monitoring camera determined to be abnormal among the monitoring cameras C _{1 to} C _n is registered in the abnormal camera DB 48. It will be. Thereafter, the process proceeds to step S90 in FIG.

  FIG. 15 shows the subroutine of step S90 of FIG. The process in step S90 is a process for displaying the monitoring camera registered in the abnormal camera DB 48 on the user terminal 14. First, in step S902 in FIG. 15, the control unit 29 acquires camera information from the abnormal camera DB 48 ((10) in FIG. 4). The camera information here is an abnormality occurrence date and camera name included in the abnormal camera DB 48 shown in FIG. Next, in step S904, the control unit 29 edits the abnormal camera list and provides it to the user terminal 14. By the editing of the control unit 29 here, a window display as shown in FIG. 18 is made on the user terminal 14. When the above processing is performed, the process returns to step S10 in FIG. Note that a user (for example, an operator) who uses the user terminal 14 selects items such as a camera name and an abnormality occurrence date and time when viewing the window display as shown in FIG. The user terminal 14 displays the video of the selected surveillance camera on the display screen of the user terminal 14 when the selection from the user or the like is received. Thereby, the user etc. can actually confirm the state (whether it is abnormal) of the selected surveillance camera.

  Next, in the camera abnormality determination unit 20, the processing performed by the state estimation unit 30 in parallel with the processing of FIG. 9 (including the processing of FIGS. 10 to 15) described above will be described with reference to FIG. It demonstrates along a flowchart. The process of FIG. 16 is a process of reviewing the contents of the abnormal camera DB 48 of FIG. 8 and reviewing the threshold η of the abnormality determination threshold DB 46 of FIG.

  First, the state estimation unit 30 acquires the camera viewing / control state in the user terminal 14 from the camera control device 12 in step S1002 of FIG. Next, in step S1004, the state estimation unit 30 determines whether or not the surveillance camera that is being viewed and controlled is registered in the abnormal camera DB 48. Here, the surveillance camera that is being viewed and controlled is a camera that is estimated to have a low possibility of being abnormal (high possibility of being normal). Therefore, there is a high possibility that the surveillance camera registered in the abnormal camera DB 48 is erroneously registered in the abnormal camera DB 48 despite the browsing / control. For this reason, when the determination in step S1004 is affirmed, the state estimation unit 30 deletes the monitoring camera from the abnormal camera DB 48 in step S1006 ((11) in FIG. 4). Further, in step S1008, the state estimation unit 30 increases the value of the threshold value η (see FIG. 7) of the monitoring camera deleted from the abnormal camera DB 48 defined in the abnormality determination threshold value DB 46 by 1% ((( 12)), the process returns to step S1002. On the other hand, if the determination in step S1004 is negative, the process directly returns to step S1002.

  In step S1008, the threshold value η is increased if the threshold value η of an erroneously registered surveillance camera is made larger (sweetened) to reduce the possibility that such erroneous registration will occur in the future. Because you can. Note that the increment of the threshold η is not limited to the above 1%, and various values can be adopted as the increment. Note that the threshold value η is set to the same value for all monitoring cameras, for example, in the initial stage of the apparatus, and the threshold value η of each monitoring camera is changed by repeated operation. .

  In the present embodiment, the case where a plurality of surveillance cameras are arranged along the road has been described. However, the present invention is not limited to this, and may be arranged along a river, a coastline, or the like.

As described above in detail, according to the present embodiment, data when the first rate-of-change calculator 22 compresses video data shot by one of the plurality of cameras C _{1 to} C _n. The amount (compressed image size) is calculated, and the rate of change S from the data amount (compressed image size) when video data previously captured by one camera is compressed is calculated (step S30), and the camera is extracted. The unit 24 extracts a camera that is within a predetermined distance (for example, within 1 km) from one camera and that captures a range of a predetermined angle (η) with reference to the direction of shooting by the one camera among a plurality of cameras. (Step S40). Then, the second rate of change calculation unit 26 calculates a data amount (compressed image size) when the video data captured by the camera extracted by the camera extraction unit 24 is compressed, and the extracted camera uses the calculated data amount. A change rate T (or an average value T ′ of change rates) is calculated from the data amount (compressed image size) when the previously captured video data is compressed (step S50). Furthermore, the abnormality determination unit 28 compares the change rate S and T (or T ′) to determine whether or not one camera is abnormal (step S60). As described above, in this embodiment, the rate of change S of the compressed image size of the video data of one camera is set to the rate of change T (or the rate of change T of the compressed image size of the camera video data located in the vicinity of the one camera. In order to compare with the average value T ′), even when the compressed image size of one camera changes due to a sudden change in weather or the like, it is possible to determine the abnormality of the camera considering such a change. Also, in order to compare the rate of change of the compressed image size in one camera with the rate of change in the compressed image size in a camera that shoots the same direction as the one camera, in the direction of the sun, that is, on the road surface, river surface, sea surface, etc. The camera abnormality can be determined in consideration of the influence on the data amount due to the reflection of sunlight. Thus, in the present embodiment, it is possible to automatically determine an abnormality of one camera with high accuracy. Further, in the present embodiment, the camera abnormality is determined by comparing with a camera having substantially the same condition without determining the camera abnormality based only on the variation amount of the change rate in one camera. Accordingly, it is possible to determine not only an abnormality such as a color bar display showing a large change rate and a plain screen display but also an abnormality such as block noise showing a small change rate.

  In addition, according to the present embodiment, when there are a plurality of cameras extracted by the camera extraction unit 24, the second change rate calculation unit 26 calculates the change rate T for the plurality of cameras and also changes the plurality of cameras. Since the average value T ′ of the rate T is calculated and this average value T ′ is compared with the rate of change S of one camera, the influence of the difference in the position of each camera and the difference in the shooting direction on the abnormality determination accuracy Can be suppressed.

  Further, according to the present embodiment, the abnormality determination unit 28 includes the change rate S calculated by the first change rate calculation unit 22 and the change rate T (average value T ′) calculated by the second change rate calculation unit 26. And the difference value exceeds the threshold value η, it is determined that one camera is abnormal. Therefore, the camera abnormality can be determined by simple calculation.

  In the present embodiment, the abnormality determination unit 28 determines whether one camera is abnormal using the threshold η corresponding to each of the plurality of cameras. Judgment can be made.

  In the present embodiment, the state estimation unit 30 estimates whether each camera is abnormal based on the usage status (viewing and control state) of video data of a plurality of cameras, and the abnormality determination unit 28 When the camera determined to be abnormal is estimated to be normal by the state estimation unit 30, the absolute value of the threshold η is greatly changed. As a result, the threshold value η is appropriately updated so that the actual camera state matches the abnormality determination result, so that the abnormality determination of the camera can be performed with higher accuracy.

  In the above-described embodiment, a case has been described in which cameras having substantially the same shooting direction are extracted as comparison targets from cameras located in the vicinity of one camera, and the average value of the change rates of the comparison target cameras is used. However, it is not limited to this. For example, among the cameras to be compared, the weighted average value is calculated by increasing the weight as the camera closer to the camera at the position and / or the camera closer to the camera as the shooting direction. It is also possible to determine whether the camera is abnormal.

  In the above embodiment, in FIG. 12, after specifying a camera located in the vicinity of one camera, a camera whose shooting direction substantially matches the shooting direction of the one camera is extracted from the specified cameras. Explained the case. However, the present invention is not limited to this. For example, after identifying a camera whose shooting direction is substantially the same as that of one camera, the camera located near the one camera is extracted from the identified cameras. Also good.

  Moreover, although the monitoring camera demonstrated the case where the surveillance camera had the swing part 4 in the said embodiment, it is not restricted to this, The imaging | photography direction may be fixed for a surveillance camera. In this case, if the shooting direction is defined in the camera metadata DB 42 corresponding to each surveillance camera, the processing of FIG. 12 can be realized without calculating the shooting direction.

  In the above embodiment, the threshold value η is set to the same value in all monitoring cameras in the initial stage, but the present invention is not limited to this. For example, different values may be set in advance based on the monitoring camera arrangement environment, the manufacturer, type, and characteristics of the monitoring camera. In this case, the value of the threshold η may not be updated as appropriate.

  In the above embodiment, the case where the abnormal camera DB 48 is reviewed based on the estimation result by the state estimation unit 30 has been described, but the present invention is not limited to this. For example, when the user or the like actually confirms the monitoring camera displayed on the screen of FIG. 18 and there is no problem, the information of the monitoring camera may be deleted from the abnormal camera DB 48. When the deletion is performed as described above, the abnormality determination unit 28 may change the threshold η of the monitoring camera deleted from the abnormal camera DB 48.

  Note that the processing and functions described above can be realized by a computer system (computer) as described above. In that case, a program describing the processing contents of the functions that the camera state monitoring apparatus 10 should have is provided. By executing the program on a computer, the above processing functions are realized on the computer. The program describing the processing contents can be recorded on a computer-readable recording medium.

  When distributing the program, for example, portable recording media such as a DVD (Digital Versatile Disc) and a CD-ROM (Compact Disc Read Only Memory) on which the program is recorded are sold. It is also possible to store the program in a storage device of a server computer and transfer the program from the server computer to another computer via a network.

  The computer that executes the program stores, for example, the program recorded on the portable recording medium or the program transferred from the server computer in its own storage device. Then, the computer reads the program from its own storage device and executes processing according to the program. The computer can also read the program directly from the portable recording medium and execute processing according to the program. Further, each time the program is transferred from the server computer, the computer can sequentially execute processing according to the received program.

  The above-described embodiment is an example of a preferred embodiment of the present invention. However, the present invention is not limited to this, and various modifications can be made without departing from the scope of the present invention.

22 first change rate calculating section 24 camera extractor 26 second change rate calculating unit 28 abnormality determination section 30 state estimating unit 100 the camera condition monitoring apparatus C ₁ -C _n surveillance camera (Camera)

Claims (7)

Calculate the amount of data when video data shot by one of a plurality of cameras is compressed, and the rate of change from the amount of data when video data shot before by the one camera is compressed A first rate-of-change calculator that calculates
A camera extraction unit that extracts a camera that is within a predetermined distance from the one camera and extracts a predetermined angle range based on a direction in which the one camera is imaged among the plurality of cameras;
The amount of data when the video data captured by the camera extracted by the camera extraction unit is compressed is calculated, and the change from the amount of data when the video data previously captured by the extracted camera is compressed is calculated. A second rate-of-change calculator that calculates the rate;
An abnormality determining unit that compares the rate of change calculated by the first rate-of-change calculating unit with the rate of change calculated by the second rate-of-change calculating unit to determine an abnormality of the one camera. Camera status monitoring device. When there are a plurality of cameras extracted by the camera extraction unit, the second change rate calculation unit calculates a change rate in the plurality of cameras and calculates an average value of the change rates in the plurality of cameras. ,
The abnormality determination unit compares the change rate calculated by the first change rate calculation unit with an average value of the change rates calculated by the second change rate calculation unit. The camera state monitoring device described.   The abnormality determination unit compares the change rate calculated by the first change rate calculation unit with the change rate calculated by the second change rate calculation unit, and an absolute value of the difference exceeds a threshold value. 3. The camera state monitoring apparatus according to claim 1, wherein the one camera is determined to be abnormal when the camera is abnormal.   The camera state monitoring apparatus according to claim 3, wherein the abnormality determination unit determines whether or not the one camera is abnormal by using a threshold corresponding to each of the plurality of cameras. Based on the usage status of the video data of the plurality of cameras, further comprising a state estimation unit that estimates whether each camera is abnormal,
The said state estimation part changes the said threshold value largely, when the camera determined to be abnormal by the said abnormality determination part is estimated normal by the said state estimation part, The said threshold value is characterized by the above-mentioned. Camera status monitoring device. Computer
Calculate the amount of data when video data shot by one of a plurality of cameras is compressed, and the rate of change from the amount of data when video data shot before by the one camera is compressed A first rate of change calculation unit for calculating
A camera extraction unit that extracts a camera that is within a predetermined distance from the one camera and extracts a predetermined angle range based on a direction in which the one camera captures, among the plurality of cameras;
The amount of data when the video data captured by the camera extracted by the camera extraction unit is compressed is calculated, and the change from the amount of data when the video data previously captured by the extracted camera is compressed is calculated. A second rate-of-change calculating unit that calculates a rate; and the rate of change calculated by the first rate-of-change calculating unit is compared with the rate of change calculated by the second rate-of-change calculating unit; A camera state monitoring program that functions as an abnormality determination unit that determines an abnormality of the camera. Calculate the amount of data when video data shot by one of a plurality of cameras is compressed, and the rate of change from the amount of data when video data shot before by the one camera is compressed A first rate-of-change calculating step for calculating
A camera extraction step of extracting a camera that is within a predetermined distance from the one camera and that captures a predetermined angle range based on a direction in which the one camera captures, among the plurality of cameras;
The amount of data when the video data captured by the camera extracted in the camera extraction step is compressed is calculated, and the change from the amount of data when the video data previously captured by the extracted camera is compressed A second change rate calculating step for calculating a rate;
An abnormality determination step of comparing the change rate calculated in the first change rate calculation step with the change rate calculated in the second change rate calculation step to determine an abnormality of the one camera. Camera status monitoring method.

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