JP2009200757A - Video data processing apparatus, program, and method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To compress video data while holding a useful part. <P>SOLUTION: A video data processing apparatus has an importance degree calculation means for calculating the importance degree of a frame image on the basis of at least a feature that the frame image has and a video data photographing condition for the respective frame images configuring the video data, and a compression means for compressing the video data on the basis of the importance degree. In such a manner, the video data is compressed considering the photographing condition (for instance, a photographing place or the like) and the feature (for instance, the movement or direction of a photographing object or the like) that the video data have. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a technique for compressing video data while retaining useful portions in the video data.

  Conventionally, for the purpose of crime prevention, for example, surveillance cameras have been installed in office entrances, elevator halls, server rooms and office rooms, banks, ATMs of convenience stores, and the like. Video captured by these surveillance cameras is converted to data and stored in storage. Later, you can check the video as needed.

  On the other hand, the amount of video data to be stored is increasing as the system becomes larger and the storage period becomes longer. However, since the storage capacity is limited, it is necessary to reduce the amount of video data, for example, by compressing data.

For example, Japanese Patent Laid-Open No. 2003-153177 discloses a video recording apparatus that maintains the quality of an image for achieving the purpose of a recorded video while suppressing the capacity of recorded data for storage. Specifically, the video recording device can change the data size by converting at least one of the frame rate, compression rate, and resolution of the recorded data, and inputs the video captured by the imaging device. Video input means, means for storing the video input by the video input means as recording data having a relatively large data size in the storage device, and recording data for which a predetermined time has elapsed since being stored in the storage device, A conversion process for reducing the data size of the recording data is performed, and means for storing the converted recording data in the storage device as new recording data in place of the original recording data.
JP 2003-153177 A

  However, in the prior art, when reducing the amount of video data, the shooting conditions and the characteristics of the video data are not taken into consideration. Therefore, there is a possibility that a part which is not very useful is left or a useful part is reduced.

  Accordingly, an object of the present invention is to provide a technique for compressing video data while retaining a useful portion in the video data.

  The video data processing device according to the present invention is an importance calculation means for calculating the importance of each frame image constituting the video data based on at least the characteristics of the frame image and the shooting conditions of the video data. And compression means for compressing the video data based on the importance.

  In this way, the video data can be compressed in consideration of the shooting conditions (for example, the shooting location) and the characteristics of the video data (for example, the movement and orientation of the shooting target). For example, for frame images where no one is shown or only the human back is shown, the image quality is reduced to reduce the amount of data, and for frame images where a human face is shown, the image quality is not reduced. By doing so, it is possible to compress the video data while retaining useful portions in the video data.

  In addition, the shooting condition may include a location point set in advance for each shooting location. Then, the importance calculation means may calculate the importance using a location point corresponding to the shooting location of the video data.

  For example, even in the case of frame images with the same shooting content, by setting the location point of a highly important place (for example, a vault) high, a less important place (for example, an elevator) Compared to a frame image obtained by shooting a hole or the like, it is possible to compress video data so that the image quality of a frame image taken at a highly important place is not deteriorated.

  Further, the importance calculation means extracts at least one of the magnitude of the movement of the portion regarded as the shooting target in the frame image and the direction of the portion regarded as the shooting target as the feature of the frame image. The importance level is calculated using at least one of a movement point corresponding to the magnitude of the movement of the part regarded as the photographing object and a direction point corresponding to the direction of the part regarded as the photographing object. May be.

  For example, when a large movement of the photographing object is detected, the video data can be compressed so as not to deteriorate the image quality of the frame image.

  In addition, when the sensor is installed at the video data shooting location, the importance calculator may calculate the importance based further on the event information detected by the sensor.

  In this way, for example, when the sensor detects unauthorized intrusion, the video data can be compressed so as not to deteriorate the image quality of the frame image at the detection time.

  Further, the importance level calculation means may calculate the importance level for the frame image at the time of event detection using an event point corresponding to the event. In addition, the importance level calculation means includes a first predetermined number of frame images before the frame image at the time of event detection, and a second predetermined number of frame images after the frame image at the time of event detection. For at least one of them, the importance may be calculated using an event point corresponding to the event.

  In this way, for example, video data can be compressed so as not to deteriorate the image quality of frame images of several seconds before and after the detection of unauthorized intrusion.

  Further, the compression means may compress the video data by thinning out the frame images whose importance is less than a predetermined standard. In addition, the lower the importance, the higher the compression rate of the frame image.

  A program for realizing the video data processing apparatus according to the present invention can be created. This program is a storage medium or storage device such as a flexible disk, a CD-ROM, a magneto-optical disk, a semiconductor memory, or a hard disk. Stored in Moreover, it may be distributed as a digital signal via a network or the like. The intermediate processing result is temporarily stored in a storage device such as a main memory.

  According to the present invention, video data can be compressed while retaining a useful portion in the video data.

  An outline of a system according to an embodiment of the present invention is shown in FIG. For example, a management server 31 and a server 51 that performs main processing in the present embodiment are connected to the network 1 that is the Internet.

  The management server 31 is provided in the entrance / exit management system 3 and can access the entrance / exit history DB 32 included in the entrance / exit management system 3. Furthermore, the management server 31 is connected to the sensor 11 installed at the monitoring point A via the network 7 which is the Internet, for example. In the present embodiment, it is assumed that the sensor 11 is installed in a door that requires authentication when entering or leaving the room and has an authentication function. The entry / exit history DB 32 stores information such as entry / exit rooms at the time of successful authentication, authentication errors, and unauthorized intrusion detected by the sensor 11.

  The server 51 is provided in the video monitoring system 5 and can access a video file storage unit 52 that is also included in the video monitoring system 5. Furthermore, the server 51 is connected to the recorder 9A installed at the monitoring point A and the recorder 9B installed at the monitoring point B via the network 7. The video file storage 52 stores the video data transmitted from the recorders 9A and 9B as a video file.

  The recorder 9A is connected to a camera 10A that is also installed at the monitoring point A, and stores video data captured by the camera 10A. The recorder 9B is connected to a camera 10B that is also installed at the monitoring point B, and stores video data captured by the camera 10B. Moreover, although the example in case the number of monitoring spots is two (monitoring spots A and B) is shown in FIG. 1, the number of monitoring spots is not limited to this.

  FIG. 2 shows a functional block diagram of the server 51 shown in FIG. The server 51 includes a video receiving unit 511 that registers video data received from the recorder 9 as a video file in the video file storage unit 52, a status DB 512 that stores status information of the video file registered by the video receiving unit 511, and an input. An event acquisition unit 513 that acquires event information (for example, entry / exit when authentication is successful, authentication error, unauthorized intrusion, etc.) from the exit management system 3, and an event DB 514 that stores event information acquired by the event acquisition unit 513 Based on the data stored in the camera DB 515 storing the information of the cameras installed at each monitoring point, the status DB 512, the event DB 514, and the camera DB 515, a video information file is generated, and the point of each frame image is obtained. Point setting unit 516 to calculate and point setting unit In response to an instruction from the video information file storage unit 517 that stores the video information file generated by the image processing unit 16 and the point setting unit 516, video analysis processing is performed on the video file stored in the video file storage unit 52. A video analysis unit 518; and a video compression unit 519 that performs compression processing on the video file stored in the video file storage unit 52 based on data stored in the status DB 512 and the video information file storage unit 517. .

  FIG. 3 shows an example of data stored in the status DB 512. In the example of FIG. 3, the status DB 512 includes a file name column and a status column. In the file name column, the file name of the video file is registered. In the status column, the status of the video file (waiting for analysis / uncompressed / compressed) is set.

  FIG. 4 shows an example of data stored in the event DB 514. In the example of FIG. 4, the event DB 514 includes a time line, a sensor ID line, and an event type line. Data acquired from the entrance / exit management system 3 is set in each row.

  FIG. 5 shows an example of data stored in the camera DB 515. In the example of FIG. 5, the camera DB 515 includes a camera ID column, a location point column, a sensor point column, a sensor ID column, and an adjustment frame number column. The sensor point columns are divided into columns for each event type (in the example of FIG. 5, an intrusion alarm column, an entry / exit column, and an authentication error column). In addition, the column of the number of adjustment frames is divided into columns for each event type (in the example of FIG. 5, an intrusion alarm column, an entry / exit column, and an authentication error column), and a pre-column and a post-column It is divided into. In the place point column, a point value corresponding to the monitoring point where the camera is installed is set, and in this embodiment, a higher point value is set for a place with higher importance. In the sensor point column, a point value corresponding to the event detected by the sensor 11 is set. In the sensor ID column, when a sensor is installed at a monitoring point where a camera is installed, the ID of the sensor is set. Note that “−” indicates that no sensor is installed at the monitoring point where the camera is installed. The number of frame images to which sensor points are to be assigned is set in the adjustment frame number column. For example, in order to give sensor points to the frame images from the frame image at the time of detection to 30 frames before the detection of the intrusion alarm, “30” is set in the pre-intrusion alarm column. Similarly, in order to give sensor points to the frame images from the frame image at the time of detection to 20 frames after the detection of the intrusion alarm, “20” is set in the column of the intrusion alarm post. The process for assigning sensor points will be described in detail later.

  FIG. 6 shows an example of a video information file stored in the video information file storage unit 517. In the example of FIG. 6, the video information file includes a time stamp line, a motion point line, a face point line, a sensor point line, a location point line, and a total point line. . The values set in each row will be described later in detail.

  FIG. 7 shows an example of a video file stored in the video file storage unit 52. As shown in FIG. 7A, the video file is composed of a header part and a data part. Further, as shown in FIG. 7B, the header part includes a frame number and a time stamp. The data portion includes a still image of each frame.

  Next, the processing of the server 51 will be described with reference to FIGS. First, processing when video data is received from the recorder 9 will be described with reference to FIGS. 8 and 9. At each monitoring point, the video data captured by the camera 10 is stored in the recorder 9, and the video data stored in the recorder 9 is transmitted to the server 51 periodically or at an arbitrary timing. The video receiver 511 of the server 51 receives the video data from the recorder 9 (FIG. 8: step S1).

  Then, the video reception unit 511 assigns a file name based on a predetermined rule, and stores the video data as a video file in the video file storage unit 52 (step S3). In this embodiment, as shown in FIG. 9, the file name is determined based on “recording start time”, “recording time”, and “camera ID”. For example, if the recording start time is “February 14, 2008 12:34:56”, the recording time is “30 minutes”, and the camera ID is “cam1”, the file name is “20080214123456_30_cam1.video”. In addition, as long as the file name can identify the video file, the file name may be assigned based on other rules. The video receiving unit 511 adds a record including the file name given by the process of step S3 to the status DB 512, and sets the status of the record to “waiting for analysis” (step S5).

  By performing the processing as described above, every time video data is received from the recorder 9, a video file is stored in the video file storage unit 52, and a record indicating that the status of the video file is “waiting for analysis” Is added to the status DB 512.

  Next, processing for calculating the importance of each frame image constituting the video file will be described with reference to FIGS. The server 51 performs processing as shown in FIGS. 10 to 13 periodically or at an arbitrary timing. Although not shown in the figure, as a premise of this process, the event acquisition unit 513 of the server 51 makes an inquiry to the management server 31 and the acquisition of event information up to the start of this process is completed. To do.

  First, the point setting unit 516 of the server 51 determines whether there is a video file whose status is “waiting for analysis” (FIG. 10: step S7). Specifically, the status DB 512 is searched to determine whether a record whose status is “waiting for analysis” is stored. If there is no video file whose status is “waiting for analysis” (step S7: No route), the process ends.

  On the other hand, when it is determined that there is a video file whose status is “waiting for analysis” (step S7: Yes route), the point setting unit 516 specifies one video file among the corresponding video files (step S9). ). Then, the point setting unit 516 generates a video information file corresponding to the specific video file based on the specific video file stored in the video file storage unit 52, and stores the video information file in the video information file storage unit 517 (step S11). At this time, the point setting unit 516 assigns a file name based on the rules shown in FIG. The file name of the video information file is the same except for the file name and extension of the corresponding video file. For example, if the file name of the corresponding video file is “20080214123456_30_cam1.video”, the file name of the video information file is “20080214123456_30_cam1.inf”. Further, the point setting unit 516 sets the time stamp of each frame image constituting the specific video file in the time stamp row (FIG. 6) of the video information file.

  Then, the point setting unit 516 specifies unprocessed frame images included in the specific video file in the order from the earliest time stamp (step S13). Then, the point setting unit 516 instructs the video analysis unit 518 to analyze the specific video file. In response to the instruction from the point setting unit 516, the video analysis unit 518 performs a motion analysis process and registers a motion point related to the specific frame image in the video information file (step S15). Specifically, the motion analysis process is performed to detect the motion of the photographing object, and the higher the detected motion, the higher the point is set. For example, a technique described in Japanese Patent Application Laid-Open No. 2002-63578 can be used as a technique for detecting the movement of the photographing object.

  In addition, the video analysis unit 518 performs face analysis processing, and registers the face point related to the specific frame image in the video information file (step S17). Specifically, by performing face analysis processing, it is judged whether a human face is reflected or facing the front, etc., and a higher point is set as the human face is larger and facing the front. To do. For example, a technique described in Japanese Patent Application Laid-Open No. 2006-338329 can be used as a technique for determining whether a human face is reflected or facing the front.

  Then, the point setting unit 516 determines whether processing has been completed for all frame images included in the specific video file (step S19). If processing has not been completed for all the frame images included in the specific video file (step S19: No route), the processing returns to step S13. On the other hand, when the process is completed for all the frame images included in the specific video file (step S19: Yes route), the process proceeds to the process of step S21 (FIG. 11) via the terminal A.

  Moving to the description of FIG. 11, after the terminal A, the point setting unit 516 extracts the camera ID from the file name of the specific video file (FIG. 11: Step S21). Then, the point setting unit 516 refers to the camera DB 515 and determines whether there is a sensor corresponding to the camera (step S23). When it is determined that there is no sensor corresponding to the camera (step S23: No route), the processing of step S25 to step 35 described later is skipped, and the processing of step S37 (FIG. 13) is performed via the terminal B. Migrate to

  On the other hand, when it is determined that there is a sensor corresponding to the camera (step S23: Yes route), the point setting unit 516 determines whether an event related to the sensor exists in the event DB 514 (step S25). When it is determined that there is no event related to the sensor in the event DB 514 (step S25: No route), the processing of step S27 to step S35 is skipped, and the processing of step S37 (FIG. 13) is performed via the terminal B. Transition.

  On the other hand, if it is determined that an event related to the sensor exists in the event DB 514 (step S25: Yes route), the point setting unit 516 extracts the shooting time related to the specific video file and temporarily stores it in the storage device ( Step S27). Specifically, the point setting unit 516 extracts time stamps of the first frame image and the last frame image of the specific video file. In addition, the point setting unit 516 specifies an unprocessed event among events related to the sensor (step S29). Then, the point setting unit 516 determines whether the occurrence time of the specific event is within the shooting time of the specific file (step S31). If it is determined that the occurrence time of the specific event is outside the shooting time of the specific file (step S31: No route), the process of step S33 is skipped and the process proceeds to step S35.

  On the other hand, when it is determined that the occurrence time of the specific event is within the shooting time of the specific file (step S31: Yes route), the point setting unit 516 performs sensor point provision processing based on the data stored in the camera DB 515. (Step S33).

  The sensor point giving process will be described with reference to FIG. The point setting unit 516 acquires a sensor point corresponding to the camera and the specific event from the camera DB 515 (FIG. 12: step S51). In addition, the point setting unit 516 acquires the number of adjustment frames (pre and post) corresponding to the camera and the specific event from the camera DB 515, and specifies a frame image to which a sensor point is to be assigned (step S53). Specifically, first, a frame image at the time of detecting a specific event is specified as a frame image to which sensor points are to be added. Further, the frame images from the frame image at the time of detecting the specific event to the previous number of adjustment frames (pre) are specified as the frame images to which sensor points are to be assigned. Further, the frame images from the frame image at the time of detecting the specific event to the number of adjustment frames (post) after are specified as frame images to which sensor points are to be assigned. And the point setting part 516 registers the sensor point which concerns on the frame image which should give a sensor point to a video information file (step S55). That is, sensor points are given not only to the frame image at the time of detecting the specific event but also to the previous and next frame images. Thereafter, the sensor point giving process ends, and the process returns to the original process.

  Returning to the description of FIG. 11, after performing the process of step S33, the point setting unit 516 determines whether the process has been completed for all the events related to the sensor (step S35). If processing has not been completed for all events related to the sensor (step S35: No route), the processing returns to step S29. On the other hand, when the process is completed for all events related to the sensor (step S35: Yes route), the process proceeds to the process of step S37 (FIG. 13) via the terminal B.

Moving to the description of FIG. 13, after the terminal B, the point setting unit 516 acquires a location point corresponding to the camera from the camera DB 515 and registers it in the video information file (FIG. 13: Step S37). Then, the point setting unit 516 calculates, for each frame image, a total point corresponding to the importance of the frame image and registers it in the video information file (step S39). In the present embodiment, the total points are calculated using the following formula.
Total points = (motion points + face points + sensor points) x location points

  Then, the point setting unit 516 sets the status of the record corresponding to the specific video file in the status DB 512 to “uncompressed” (step S41). Thereafter, the process returns to the process of step S7 (FIG. 10) via the terminal C.

  For example, FIGS. 14 to 16 show examples of calculation results of importance (total points). FIG. 14A shows an image of a scene where a person enters the room after authentication. FIG. 14B shows points corresponding to the frame images in FIG. In FIG. 14B, the total points are higher for frame images that are easier to identify a person (for example, frames 7 and 8). This is because the face point is higher in an image in which a person's face is clearly shown.

  FIG. 15A is an image when the authentication error is detected, although the shooting location is the same as FIG. 14A. FIG. 15B shows points corresponding to the respective frame images in FIG. In FIG. 15B, the sensor point is high for the frame image at the time of detecting the authentication error and the frame images before and after the authentication error. Therefore, for example, the frame 8 in FIG. 14A and the frame 6 in FIG. 15A are similar frame images, but the total points are higher in the frame 6 in FIG. 15A. ing.

  Further, FIG. 16A is an image obtained by photographing a highly important place. FIG. 16B shows points corresponding to the respective frame images in FIG. The frame image in FIG. 16 (a) is the same as the frame image in FIG. 14 (a), but since the location point is higher, the frame image in FIG. 16 (a) has a higher total point.

  By performing the processing as described above, the importance (total points) in consideration of the shooting location, the movement and orientation of the shooting target, and the event can be calculated for each frame image.

  Next, processing for compressing a video file will be described with reference to FIGS. 17 and 18. The server 51 performs processing as shown in FIGS. 17 and 18 periodically or at an arbitrary timing. First, the video compression unit 519 of the server 51 determines whether there is a video file whose status is “uncompressed” (FIG. 17: step S57). More specifically, the status DB 512 is searched to determine whether or not a record whose status is “uncompressed” is stored. If there is no video file whose status is “uncompressed” (step S57: No route), the process proceeds to step S69 (FIG. 18) via the terminal D.

  On the other hand, when it is determined that there is a video file whose status is “uncompressed” (step S57: Yes route), the video compression unit 519 identifies an unprocessed video file among the corresponding video files (step S57). S59). Then, the video compression unit 519 determines whether or not a first predetermined period has elapsed from the shooting date of the specific video file (step S61). If the first predetermined period has not elapsed since the shooting date of the specific video file (step S61: No route), the processing of step S63 and step S65, which will be described later, is skipped, and the process proceeds to step S67.

  On the other hand, when the first predetermined period has elapsed from the shooting date of the specific video file (step S61: Yes route), the video compression unit 519 performs the process on the specific file based on the video information file corresponding to the specific video file. A compression process is performed (step S63). Specifically, the video file is compressed by thinning out frame images whose total points registered in the video information file are less than a predetermined value, or increasing the compression rate as the total points are lower. Note that the compression method is not different from the conventional method, and is not described here any further. Then, the video compression unit 519 sets the status of the record corresponding to the specific video file in the status DB 512 to “compressed” (step S65). Although not shown in the drawing, the date and time when the compression processing was performed may be registered in the status DB 512.

  Then, the video compression unit 519 determines whether the processing has been completed for all corresponding video files (step S67). If the processing has not been completed for all corresponding video files (step S67: No route), the processing returns to step S59. On the other hand, when the processing has been completed for all corresponding video files (step S67: Yes route), the processing proceeds to the processing of step S69 (FIG. 18) via the terminal D.

  Moving to the description of FIG. 18, after the terminal D, the video compression unit 519 determines whether there is a video file whose status is “compressed” (FIG. 18: step S69). Specifically, the status DB 512 is searched to determine whether a record whose status is “compressed” is stored. If there is no video file whose status is “compressed” (step S69: No route), the processing of steps S71 to 77 described later is skipped, and this processing ends.

  On the other hand, when it is determined that there is a video file whose status is “compressed” (step S69: Yes route), the video compression unit 519 identifies an unprocessed video file among the corresponding video files (step S69). S71). Then, the video compression unit 519 determines whether or not a second predetermined period has elapsed from the shooting date of the specific video file (step S73). If the first predetermined period has not elapsed since the shooting date of the specific video file (step S73: No route), the process of step S75 described later is skipped, and the process proceeds to step S77.

  On the other hand, when the second predetermined period has elapsed from the shooting date of the specific video file (step S73: Yes route), the video compression unit 519 performs the process on the specific file based on the video information file corresponding to the specific video file. A compression process is performed (step S75). The process of step S75 is basically the same as the process of step S63 described above, but the compression rate is increased or the reference predetermined value is increased compared to the process of step S63. . That is, here, the compressed video file is further compressed.

  Then, the video compression unit 519 determines whether the processing has been completed for all corresponding video files (step S77). If the processing has not been completed for all corresponding video files (step S77: No route), the processing returns to step S71. On the other hand, when the processing has been completed for all corresponding video files (step S77: Yes route), this processing ends.

  By performing the processing as described above, compression can be performed without changing the image quality of highly important frame images. That is, it is possible to compress while retaining useful information.

  Although one embodiment of the present invention has been described above, the present invention is not limited to this. For example, the functional block diagram described above does not necessarily correspond to an actual program module configuration. The management server 31 and the server 51 may be realized by a plurality of computers instead of a single computer.

  Further, the configuration of each table described above is an example, and the configuration as described above is not necessarily required. Further, in the processing flow, the processing order can be changed if the processing result does not change. Further, it may be executed in parallel.

  In the above description, an example in which the number of times of compression is two (that is, compression after the elapse of the first predetermined period and compression after the elapse of the second predetermined period) has been described. It is not limited. For example, a video file that captures a highly important place may be compressed only once, and a video file that captures a less important place may be compressed multiple times (for example, three times or more).

  The formula for calculating the total points is an example, and the total points may be calculated using other formulas.

  The management server 31 and the server 51 are computer devices as shown in FIG. 19, and a display connected to a memory 2501 (storage device), a CPU 2503 (processing device), a hard disk drive (HDD) 2505, and a display device 2509. A control unit 2507, a drive device 2513 for a removable disk 2511, an input device 2515, and a communication control unit 2517 for connecting to a network are connected by a bus 2519. An operating system (OS: Operating System) and an application program for performing processing in the present embodiment are stored in the HDD 2505, and are read from the HDD 2505 to the memory 2501 when executed by the CPU 2503. If necessary, the CPU 2503 controls the display control unit 2507, the communication control unit 2517, and the drive device 2513 to perform necessary operations. Further, data in the middle of processing is stored in the memory 2501 and stored in the HDD 2505 if necessary. In the embodiment of the present invention, an application program for performing the processing described above is stored in the removable disk 2511 and distributed, and is installed in the HDD 2505 from the drive device 2513. In some cases, the HDD 2505 may be installed via a network such as the Internet and the communication control unit 2517. Such a computer apparatus realizes various functions as described above by organically cooperating hardware such as the CPU 2503 and the memory 2501 described above, the OS, and necessary application programs.

(Appendix 1)
Importance calculation means for calculating the importance of the frame image based on at least the characteristics of the frame image and the shooting conditions of the video data for each frame image constituting the video data;
Compression means for compressing the video data based on the importance;
A video data processing apparatus.

(Appendix 2)
The shooting conditions include a location point preset for each shooting location,
The importance calculating means is
The video data processing apparatus according to claim 1, wherein the importance is calculated using the location point corresponding to the shooting location of the video data.

(Appendix 3)
The importance calculating means is
As the feature of the frame image, extract at least one of the magnitude of the movement of the part regarded as the photographing object in the frame image and the direction of the part regarded as the photographing object,
The importance is calculated using at least one of a movement point corresponding to the magnitude of the movement of the part regarded as the photographing object and a direction point corresponding to the direction of the part regarded as the photographing object. The video data processing apparatus according to supplementary note 1, wherein:

(Appendix 4)
The importance calculating means is
The video data processing apparatus according to appendix 1, wherein when a sensor is installed at the video data shooting location, the degree of importance is further calculated based on event information detected by the sensor.

(Appendix 5)
The importance calculating means is
The video data processing apparatus according to appendix 4, wherein the importance level is calculated for the frame image at the time of the event detection using an event point corresponding to the event.

(Appendix 6)
The importance calculating means is
At least one of the first predetermined number of the frame images before the frame image at the time of the event detection, and a second predetermined number of the frame images after the frame image at the time of the event detection. The video data processing apparatus according to appendix 5, wherein the importance is calculated using an event point corresponding to the event.

(Appendix 7)
The compression means comprises:
The video data processing apparatus according to claim 1, wherein the video data is compressed by thinning out the frame images having the importance less than a predetermined reference.

(Appendix 8)
The video data processing apparatus according to appendix 1, wherein the lower the importance, the higher the compression rate of the frame image.

(Appendix 9)
For each frame image constituting the video data, an importance calculation step for calculating the importance of the frame image based on at least the characteristics of the frame image and the shooting conditions of the video data;
A compression step of compressing the video data based on the importance;
A video data processing program for causing a computer to execute.

(Appendix 10)
For each frame image constituting the video data, an importance calculation step for calculating the importance of the frame image based on at least the characteristics of the frame image and the shooting conditions of the video data;
A compression step of compressing the video data based on the importance;
A video data processing method executed by a computer.

It is a system configuration figure concerning an embodiment of the invention. It is a functional block diagram of a server in an embodiment of the invention. It is a figure which shows an example of the data stored in status DB. It is a figure which shows an example of the data stored in event DB. It is a figure which shows an example of the data stored in camera DB. It is a figure which shows an example of a video information file. (A) And (b) is a figure which shows an example of a video file. It is a figure which shows the processing flow at the time of video data reception. It is a figure for demonstrating the naming rule of a file name. It is a figure which shows the processing flow (1st part) of the process which calculates importance. It is a figure which shows the processing flow (2nd part) of the process which calculates importance. It is a figure which shows the processing flow of a sensor point provision process. It is a figure which shows the processing flow (3rd part) of the process which calculates importance. (A) And (b) is a figure which shows an example of the calculation result of importance. (A) And (b) is a figure which shows an example of the calculation result of importance. (A) And (b) is a figure which shows an example of the calculation result of importance. It is a figure which shows the processing flow (1st part) at the time of compressing a video file. It is a figure which shows the processing flow (2nd part) at the time of compressing a video file. It is a functional block diagram of a computer.

Explanation of symbols

1, 7 Network 3 Entrance / exit management system 5 Video monitoring system 9 Recorder 10 Camera 11 Sensor 31 Management server 32 Entrance / exit history DB
51 Server 52 Video File Storage Unit 511 Video Reception Unit 512 Status DB
513 event acquisition unit 514 event DB
515 Camera DB 516 Point setting unit 517 Video information file storage unit 518 Video analysis unit 519 Video compression unit

Claims (7)

Importance calculation means for calculating the importance of the frame image based on at least the characteristics of the frame image and the shooting conditions of the video data for each frame image constituting the video data;
Compression means for compressing the video data based on the importance;
A video data processing apparatus. The shooting conditions include a location point preset for each shooting location,
The importance calculating means is
The video data processing apparatus according to claim 1, wherein the importance is calculated using the location point corresponding to a shooting location of the video data. The importance calculating means is
As the feature of the frame image, extract at least one of the magnitude of the movement of the part regarded as the photographing object in the frame image and the direction of the part regarded as the photographing object,
The importance is calculated using at least one of a movement point corresponding to the magnitude of the movement of the part regarded as the photographing object and a direction point corresponding to the direction of the part regarded as the photographing object. The video data processing apparatus according to claim 1, wherein: The importance calculating means is
The video data processing apparatus according to claim 1, wherein, when a sensor is installed at a shooting location of the video data, the importance level is further calculated based on information of an event detected by the sensor. . The importance calculating means is
The video data processing apparatus according to claim 4, wherein the importance level of the frame image at the time of the event detection is calculated using an event point corresponding to the event. For each frame image constituting the video data, an importance calculation step for calculating the importance of the frame image based on at least the characteristics of the frame image and the shooting conditions of the video data;
A compression step of compressing the video data based on the importance;
A video data processing program for causing a computer to execute. For each frame image constituting the video data, an importance calculation step for calculating the importance of the frame image based on at least the characteristics of the frame image and the shooting conditions of the video data;
A compression step of compressing the video data based on the importance;
A video data processing method executed by a computer.

Images