Data deletion processing method and device, equipment and medium

Abstract

The invention discloses a data deletion processing method and device, equipment and a medium, which are used for retaining more valuable video data under the condition of saving a storage space. The method provided by the invention comprises the following steps: acquiring video data of a first time period collected for a target scene; based on video data of a second time period corresponding to the target scene, performing repeatability evaluation on the video data of the first time period to obtain a repeatability evaluation result of the video data of the first time period; and performing event detection on the video data of the first time period, and performing importance evaluation on the video data of the first time period to obtain an importance evaluation result of the video data of the first time period, and performing data deletion processing on the video data of the first time period based on the repeatability evaluation result of the video data of the first time period and / or the importance evaluation result of the video data of the first time period.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a data deletion processing method, device, equipment and medium. Background Art

[0002] At present, security has become a closely related content in daily life, and monitoring can be seen basically everywhere. One of the functions of monitoring is to see the monitoring content of historical moments, which can be stored in the cloud or locally. Summary of the invention

[0003] The embodiments of the present application provide a data deletion processing method, apparatus, device and medium for deleting video data based on evaluating the repetitiveness and importance of the video data content, thereby retaining more valuable video data while saving storage space.

[0004] A data deletion processing method provided in an embodiment of the present application includes:

[0005] Acquire video data of a first period of time collected for a target scene;

[0006] Based on the video data of the second time period corresponding to the target scene, performing repeatability evaluation on the video data of the first time period to obtain a repeatability evaluation result of the video data of the first time period; and performing importance evaluation on the video data of the first time period by performing event detection on the video data of the first time period to obtain an importance evaluation result of the video data of the first time period;

[0007] Based on the repeatability evaluation result of the video data of the first time period and / or the importance evaluation result of the video data of the first time period, data reduction processing is performed on the video data of the first time period.

[0008] The data deletion processing method provided in the embodiment of the present application obtains the video data of the first time period collected for the target scene, and based on the video data of the second time period corresponding to the target scene, performs repeatability evaluation on the video data of the first time period to obtain the repeatability evaluation result of the video data of the first time period; and performs event detection on the video data of the first time period, performs importance evaluation on the video data of the first time period to obtain the importance evaluation result of the video data of the first time period; thus, based on the repeatability evaluation result of the video data of the first time period and / or the importance evaluation result of the video data of the first time period, data deletion processing can be performed on the video data of the first time period. It can be seen that the embodiment of the present application realizes the deletion of video data based on evaluating the repeatability and importance of the video data content, thereby retaining more valuable video data while saving storage space, facilitating the maintenance of video data and the subsequent search and application of video data by users.

[0009] In some embodiments, based on the video data of the second time period corresponding to the target scene, the video data of the first time period is evaluated for repeatability to obtain a repeatability evaluation result, including:

[0010] Compare the video data of the first time period with the video data of the second time period acquired for the same target scene to obtain at least one comparison result:

[0011] Based on the at least one comparison result, obtaining a repeatability evaluation result of the video data in the first time period;

[0012] The at least one comparison result includes one or a combination of the following parameters:

[0013] A similarity evaluation parameter between the image background in the video data of the first period and the image background in the video data of the second period;

[0014] A consistency evaluation parameter of a target in the video data of the first period of time and a target in the video data of the second period of time;

[0015] An evaluation parameter for the degree of similarity between the target type in the video data of the first period and the target type in the video data of the second period;

[0016] The degree to which the event type in the video data of the first time period is similar to the event type in the video data of the second time period is evaluated by a parameter.

[0017] In some embodiments, by detecting events in the video data of the first time period, performing importance evaluation on the video data of the first time period to obtain an importance evaluation result includes:

[0018] Performing event detection on the video data of the first time period to obtain at least one event;

[0019] Determining event content importance evaluation parameters of video data of the first time period based on the type and occurrence time period of the at least one event;

[0020] Determining, based on the occurrence area of ​​the at least one event, an area-based importance evaluation parameter of the video data of the first time period;

[0021] An importance evaluation result of the video data of the first time period is determined based on the event content importance evaluation parameter of the video data of the first time period and the region-based importance evaluation parameter of the video data of the first time period.

[0022] In some embodiments, determining the event content importance evaluation parameter of the video data of the first time period based on the type and occurrence time period of the at least one event includes:

[0023] Based on the type and occurrence period of the at least one event, the at least one event is divided into a plurality of groups of events; and for each group, based on the number and occurrence period of the events in the group, an event density of the group of events based on the time dimension is determined;

[0024] Determine the density of the overall events based on the time dimension based on the number and time period of all the events;

[0025] For each type, based on the number and occurrence period of events of this type, determine the density of events of this type based on the time dimension;

[0026] Based on the event density of each group of events based on the time dimension, the density of the overall events based on the time dimension, and the density of each type of events based on the time dimension, event content importance evaluation parameters of the video data of the first time period are determined.

[0027] In some embodiments, determining the region-based importance evaluation parameter of the video data of the first time period based on the occurrence region of the at least one event includes:

[0028] Based on the occurrence area of ​​the at least one event, determine the number of events in a preset key area in the picture and the number of events in a non-key area; based on the number of events in the key area and the area of ​​the key area, and the number of events in the non-key area and the area of ​​the non-key area, determine the overall event density based on the area;

[0029] Determine an event active region on the screen of the video data of the first time period, and determine the event density in the event active region based on the number of events in the event active region and the area of ​​the event active region;

[0030] Determine the ratio of the overlapping area between the key area and the event active area to the entire screen;

[0031] Based on the region-based density of the overall events, the event density within the event active region, and the ratio, a region-based importance evaluation parameter of the video data of the first time period is determined.

[0032] In some embodiments, based on the repetitiveness evaluation result of the video data in the first period and / or the importance evaluation result of the video data in the first period, performing data deletion processing on the video data in the first period includes:

[0033] When the repeatability evaluation result is greater than a preset threshold, performing frame skipping processing on the video data of the first time period;

[0034] When the importance evaluation result is greater than a preset threshold, re-encoding the video data of the first period according to preset encoding parameters;

[0035] When the importance evaluation result is less than a preset threshold, frame dropping processing is performed on the video data of the first time period.

[0036] In some embodiments, based on the repetitiveness evaluation result of the video data in the first period and / or the importance evaluation result of the video data in the first period, performing data deletion processing on the video data in the first period further includes:

[0037] When the repeatability evaluation result is less than a preset threshold, determine whether the event density in the event active area is greater than the preset threshold. If so, re-encode the video data in the event active area and discard the video data in the non-event active area; otherwise, perform frame skipping on the video data of the first time period.

[0038] An embodiment of the present application provides a data deletion processing device, comprising:

[0039] The first unit is used to obtain video data of a first period of time collected for a target scene;

[0040] The second unit is used to perform repeatability evaluation on the video data of the first time period based on the video data of the second time period corresponding to the target scene, and obtain a repeatability evaluation result of the video data of the first time period; and to perform importance evaluation on the video data of the first time period by performing event detection on the video data of the first time period, and obtain an importance evaluation result of the video data of the first time period;

[0041] The third unit is used to perform data deletion processing on the video data of the first time period based on the repeatability evaluation result of the video data of the first time period and / or the importance evaluation result of the video data of the first time period.

[0042] Another embodiment of the present application provides an electronic device, which includes a memory and a processor, wherein the memory is used to store program instructions, and the processor is used to call the program instructions stored in the memory and execute any of the above methods according to the obtained program.

[0043] Another embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable the computer to execute any of the above methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1 A schematic diagram of the overall process of a data deletion processing method provided in an embodiment of the present application;

[0046] Figure 2 A schematic diagram of the data collection process provided in the embodiment of the present application;

[0047] Figure 3 A schematic diagram of a data comparison process provided in an embodiment of the present application;

[0048] Figure 4 A schematic diagram of grid area division for a screen provided in an embodiment of the present application;

[0049] Figure 5 A schematic diagram of a process for determining the importance evaluation result of video data provided in an embodiment of the present application;

[0050] Figure 6A schematic diagram of a process for determining event content importance evaluation parameters of video data provided in an embodiment of the present application;

[0051] Figure 7 A schematic diagram of event grouping provided in an embodiment of the present application;

[0052] Figure 8 A schematic diagram of a process for determining region-based importance evaluation parameters of video data provided in an embodiment of the present application;

[0053] Fig. 9 A schematic diagram of a specific process of data deletion processing provided in an embodiment of the present application;

[0054] Fig.10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0055] Fig.11 A schematic diagram of the structure of a data deletion processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0057] The embodiments of the present application provide a data deletion processing method, apparatus, device and medium for deleting video data based on evaluating the repetitiveness and importance of the video data content, thereby retaining more valuable video data while saving storage space.

[0058] Among them, the method and the device, equipment, and medium are based on the same application concept. Since the principles of solving problems by the method and the device, equipment, and medium are similar, the implementation of the device, equipment, medium, and method can refer to each other, and the repeated parts will not be repeated.

[0059] The terms "first", "second", etc. (if any) in the specification and claims of the embodiments of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than the content illustrated or described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0060] The following examples and embodiments are to be understood as illustrative examples only. Although this specification may refer to "one", "an" or "some" examples or embodiments in several places, this does not mean that each such reference relates to the same example or embodiment, nor does it mean that the feature applies only to a single example or embodiment. Individual features of different embodiments may also be combined to provide other embodiments. In addition, terms such as "including" and "comprising" should be understood as not limiting the described embodiments to only those features that have been mentioned; such examples and embodiments may also include features, structures, units, modules, etc. that are not specifically mentioned.

[0061] The following is a detailed description of each embodiment of the present application in conjunction with the accompanying drawings. It should be noted that the display order of the embodiments of the present application only represents the order of the embodiments, and does not represent the advantages and disadvantages of the technical solutions provided by the embodiments.

[0062] The preservation of historical monitoring data has always been a core function of the security industry, and how to reduce the disk usage of monitoring data is also a key issue to consider. Storage will inevitably involve storage media, which are not unlimited. No matter how advanced the storage technology is, the disk space will always be full, and the charges are also based on the space. The space determines the storage time of the video. When the space is full, it will be fully covered, that is, the latest data will cover the historical data, so it will be impossible to view the historical data. In order to minimize the occurrence of this situation, the embodiment of the present application tries to preserve historical information as much as possible, and performs full coverage of the data by evaluating the importance and repeatability of the data. Different full coverage methods can be adopted through the evaluation of the value of the data, such as re-editing, frame skipping, clearing (i.e. discarding), etc., to save storage space as much as possible and retain more valuable data. At the same time, the time dimension is extended as much as possible to ensure the continuity of the data timeline, so that users can find the required historical information.

[0063] See also Figure 1, a data deletion processing method provided in an embodiment of the present application includes:

[0064] S101, obtaining video data of a first period collected for a target scene;

[0065] S102, based on the video data of the second time period corresponding to the target scene, performing repeatability evaluation on the video data of the first time period to obtain a repeatability evaluation result of the video data of the first time period; and performing importance evaluation on the video data of the first time period by performing event detection on the video data of the first time period to obtain an importance evaluation result of the video data of the first time period;

[0066] The video data in the first period is the video data to be processed;

[0067] The video data of the second period is, for example, video data collected after the video data of the first period for monitoring the same target scene, that is, in terms of time, the video data of the first period is older than the video data of the second period, so the video data of the first period needs to be used as the video data to be processed and deleted;

[0068] Of course, the video data of the second time period may also be the video data before the video data of the first time period, which is not limited in the specific embodiment of the present application.

[0069] S103: Based on the repeatability evaluation result of the video data in the first period of time and / or the importance evaluation result of the video data in the first period of time, perform data deletion processing on the video data in the first period of time.

[0070] In some embodiments, based on the video data of the second time period corresponding to the target scene, the video data of the first time period is evaluated for repeatability to obtain a repeatability evaluation result, including:

[0071] Compare the video data of the first time period with the video data of the second time period acquired for the same target scene to obtain at least one comparison result:

[0072] Based on the at least one comparison result, obtaining a repeatability evaluation result of the video data in the first time period;

[0073] The at least one comparison result includes one or a combination of the following parameters:

[0074] A similarity evaluation parameter between the image background in the video data of the first period and the image background in the video data of the second period;

[0075] A consistency evaluation parameter of a target in the video data of the first period of time and a target in the video data of the second period of time;

[0076] An evaluation parameter for the degree of similarity between the target type in the video data of the first period and the target type in the video data of the second period;

[0077] The degree to which the event type in the video data of the first time period is similar to the event type in the video data of the second time period is evaluated by a parameter.

[0078] In some embodiments, based on the video data of the second time period corresponding to the target scene, the video data of the first time period is evaluated for repeatability to obtain a repeatability evaluation result, for example, including the following three stages:

[0079] Phase 1: Data collection process, see Figure 2 , for example:

[0080] S201, dividing the picture into multiple areas;

[0081] S202, performing depth detection on the content in each area of ​​the video data of the first time period and the video data of the second time period;

[0082] For example, traditional detection (grayscale detection) and AI detection can be included;

[0083] S203, for the video data of the first time period and the video data of the second time period, classify each block of regional images as an image of a changing region or an image of a stable region;

[0084] For example, for images with grayscale and / or content changes less than a threshold area, they are classified as images in the stable area; otherwise, they are classified as images in the changing area;

[0085] S204, determining target information of the video data of the first time period and the video data of the second time period by performing target recognition on the video data of the first time period and the video data of the second time period;

[0086] The target information includes, for example, target characteristics, type information, etc.

[0087] S205, determining event information of the video data of the first time period and the video data of the second time period by performing event recognition on the video data of the first time period and the video data of the second time period;

[0088] The event information includes, for example, the occurrence time, type, and characteristics of the event.

[0089] Phase 2: Data comparison process, see Figure 3 , for example:

[0090] S301. Compare stable regions of video data of a first period of time and video data of a second period of time to obtain similarity evaluation parameters of image backgrounds in the video data of the first period of time and image backgrounds in the video data of the second period of time.

[0091] The stable area can be regarded as the image background area, and step S301 includes, for example:

[0092] Determine the overlap area between the stable region image of the video data of the first period and the stable region image of the video data of the second period; for example Figure 4 As shown, assuming that the picture is divided into 16 regions in total, if regions 1 to 11 of the video data of the first period are stable regions, and regions 1 to 10 of the video data of the second period are stable regions, then regions 1 to 10 are the overlapping regions;

[0093] Calculate the ratio f1 of the overlapped area to the entire image;

[0094] Calculate the image content similarity f2 of the overlapped area; for example, compare the image content in areas 1 to 10 of the video data of the first period with the image content in areas 1 to 10 of the video data of the second period, thereby obtaining the similarity of the image contents of the two;

[0095] Based on f1 and f2, calculate a similarity evaluation parameter f3 between the image background in the video data of the first period and the image background in the video data of the second period;

[0096] For example: f3=f1*f2.

[0097] S302: Determine consistency evaluation parameters of a target in video data of a first period of time and a target in video data of a second period of time.

[0098] By comparing the target information of the video data of the first period of time and the target information of the video data of the second period of time, the consistency evaluation parameters of the target in the video data of the first period of time and the target in the video data of the second period of time can be determined, for example, including:

[0099] Identifying the same target in the video data of the first period and the video data of the second period;

[0100] Calculate the ratio of the number of the same object in the video data of the first time period and the video data of the second time period to the total number of objects in the video data of the first time period and / or the video data of the second time period;

[0101] This ratio is used as a consistency evaluation parameter f4 between the target in the video data of the first period and the target in the video data of the second period.

[0102] In some embodiments, the ratio may be multiplied by a preset constant to obtain f4.

[0103] S303, determining an evaluation parameter of the degree of similarity between the target type in the video data of the first period and the target type in the video data of the second period;

[0104] Determine the number of objects of the same type in the video data of the first period and the video data of the second period;

[0105] Calculate the number of objects of the same type in the video data of the first period and the video data of the second period, and the ratio thereof to the total number of all objects in the video data of the first period and / or the video data of the second period;

[0106] The ratio is used as a parameter f5 for evaluating the degree of similarity between the target type in the video data of the first period and the target type in the video data of the second period;

[0107] In some embodiments, the ratio may be multiplied by a preset constant to obtain f5.

[0108] S304: Determine an event type in the video data of the first period, and an evaluation parameter of the degree of similarity between the event type in the video data of the second period.

[0109] Determine the number of events of the same type in the video data of the first time period and the video data of the second time period;

[0110] Calculate the number of events of the same type in the video data of the first period and the video data of the second period, and the ratio thereof to the total number of all events in the video data of the first period and / or the video data of the second period;

[0111] The ratio is used as a parameter f6 for evaluating the degree of similarity between the target type in the video data of the first period and the target type in the video data of the second period;

[0112] In some embodiments, the ratio may be multiplied by a preset constant to obtain f6.

[0113] Phase 3: Overall computational evaluation.

[0114] Based on at least one comparison result in the above stage 2, a repeatability evaluation result of the video data in the first period is obtained.

[0115] For example, the following formula 1 is used to calculate the repeatability evaluation result f(r) of the video data in the first period:

[0116] f(r)=a1*f3+b1*f4+c1*f5+d1*f6Formula 1

[0117] Among them, a1, b1, c1, and d1 are all preset values, i.e., proportion adjustment parameters, which can be adjusted according to different scenarios, that is, the difference in weight can be adjusted. For key types and events that users pay attention to, the evaluation ratio of each comparison result can be improved.

[0118] In some embodiments, by detecting events in the video data of the first time period, importance evaluation is performed on the video data of the first time period to obtain an importance evaluation result, see Figure 5 ,include:

[0119] S501, performing event detection on the video data of the first time period to obtain at least one event;

[0120] S502: Determine an event content importance evaluation parameter of the video data of the first time period based on the type and occurrence time period of the at least one event;

[0121] S503: determining a region-based importance evaluation parameter of the video data of the first time period based on the occurrence region of the at least one event;

[0122] S504: Determine an importance evaluation result of the video data of the first time period based on the event content importance evaluation parameters of the video data of the first time period and the region-based importance evaluation parameters of the video data of the first time period.

[0123] In some embodiments, based on the type and occurrence period of the at least one event, an event content importance evaluation parameter of the video data of the first period is determined (ie, step S502), see Figure 6 ,include:

[0124] S601, dividing the at least one event into multiple groups of events based on the type and occurrence period of the at least one event;

[0125] For example, see Figure 7 According to the time period when the event occurs (key period, regular period) and the type of event (special event, regular event), the events are distinguished in two dimensions, and a total of four situations are divided, namely Figure 7 Each quadrant corresponds to a situation, that is, a group.

[0126] S602: for each group, based on the number and occurrence period of events in the group, determine the event density of the group of events based on the time dimension;

[0127] For example, see Figure 7For events in the first quadrant, calculate the ratio of the number of events in the first quadrant f(e) to the key period t to obtain the event density fn corresponding to the first quadrant, that is, the event density of this group of events based on the time dimension, that is, fn=f(e) / t.

[0128] The same goes for other groups and I will not go into details.

[0129] S603, determining the density of the overall events based on the time dimension based on the number and the time period of occurrence of all the events;

[0130] That is to say, step S603 does not distinguish between event types, and takes the ratio fq1 of the total number of all events in the video data of the first time period f(Ea) to the first time period t1 as the density of the overall events of the video data of the first time period based on the time dimension, that is, fq1=f(Ea) / t1.

[0131] S604: for each type, based on the number and occurrence period of events of the type, determine the density of events of the type based on the time dimension;

[0132] That is, step S604 distinguishes event types, and for each type, calculates the total number of events of this type f(Ea') and the ratio fq2 to the first time period t1 as the density of events of this type based on the time dimension, that is, fq2=f(Ea') / t1.

[0133] S605: Determine event content importance evaluation parameters of the video data of the first time period based on the event density of each group of events based on the time dimension, the density of the overall events based on the time dimension, and the density of each type of events based on the time dimension.

[0134] For example, the event content importance evaluation parameter fs1 of the video data in the first period is calculated using the following formula 2:

[0135] fs1=a2*fn+b2*fq1+c2*fq2Formula 2

[0136] Among them, a2, b2, and c2 are all preset values, i.e., proportional adjustment parameters, which can be adjusted according to different scenarios, that is, the difference in weight can be adjusted.

[0137] In some embodiments, based on the occurrence area of ​​the at least one event, the importance evaluation parameter based on the area of ​​the video data of the first time period is determined (ie, step S503), see Figure 8 ,include:

[0138] S801, based on the occurrence area of ​​at least one event, determining the number of events A in a preset key area and the number of events B in a non-key area in the picture;

[0139] The key area may be an image area preset by a user;

[0140] That is, in this step, the events of the video data in the first period are divided into events in the key area and events in the non-key area, and the number of events in each area is counted.

[0141] S802, determining the overall event density fa1 based on the number of events A in the key area and the area s1 of the key area, and the number of events B in the non-key area and the area s2 of the non-key area;

[0142] For example, the following formula 3 is used to calculate the overall event density fa1 based on the region:

[0143] fa1=a3*A / s1+b3*B / s2Formula 3

[0144] Among them, a3 and b3 are both preset values, i.e., proportional adjustment parameters, which can be adjusted according to different scenarios, that is, the difference in weight can be adjusted.

[0145] S803, determining an event active area on the screen of the video data of the first time period;

[0146] The event active area, that is, the hot spot active area, is, for example, a driving area on a street, an intersection, and the like.

[0147] Point statistics can be performed based on the location where the event occurred. For image areas where the number of events exceeds a preset threshold, they can be marked as event active areas, and the location, area, etc. of the event active area, as well as the number of events contained in the event active area, can be recorded.

[0148] S804, determining an event density fa2 in the event active area based on the number of events C in the event active area and the area s3 of the event active area;

[0149] For example, the event density fa2 in the event active area is calculated using the following formula 4:

[0150] fa2=a4*C / s3Formula 4

[0151] Of course, it is also possible to directly calculate fa2=f(n) / s3 without multiplying by the preset value.

[0152] S805, determining the ratio f(s) of the overlapping area between the key area and the event active area to the entire screen;

[0153] S806: Determine a region-based importance evaluation parameter of the video data of the first time period based on the region-based density of the overall events, the event density in the event active region, and the ratio.

[0154] For example, the following formula 5 is used to calculate the region-based importance evaluation parameter fs2 of the video data in the first period:

[0155] fs2=a5*fa1+b5*fa2+c5*f(s) Formula 5

[0156] Among them, a5, b5, and c5 are all preset values, i.e., proportional adjustment parameters, which can be adjusted according to different scenarios, that is, the difference in weight can be adjusted.

[0157] In some embodiments, determining the importance evaluation result of the video data of the first time period based on the event content importance evaluation parameter of the video data of the first time period and the region-based importance evaluation parameter of the video data of the first time period (i.e., step S504) includes:

[0158] For example, the importance evaluation result f(y) of the video data in the first period is calculated using the following formula 6:

[0159] f(y)=a6*fs1+b6*fs2Formula 6

[0160] Among them, a6 and b6 are both preset values, i.e., proportional adjustment parameters, which can be adjusted according to different scenarios, that is, the difference in weight can be adjusted.

[0161] In some embodiments, based on the repetitiveness evaluation result of the video data in the first period and / or the importance evaluation result of the video data in the first period, performing data deletion processing on the video data in the first period includes:

[0162] When the repeatability evaluation result is greater than a preset threshold, performing frame skipping processing on the video data of the first time period;

[0163] When the importance evaluation result is greater than a preset threshold, re-encoding the video data of the first period according to preset encoding parameters;

[0164] When the importance evaluation result is less than a preset threshold, frame dropping processing is performed on the video data of the first time period.

[0165] It should be noted that in the embodiment of the present application, the preset thresholds appearing at different locations may be the same or different.

[0166] The re-encoding process described in the embodiment of the present application is to re-encode the data after decoding, and discard part of the data by changing the encoding parameters, such as resolution, bit rate and other information;

[0167] The frame loss processing described in the embodiment of the present application is to discard part of the data (for example, discard all unnecessary P frames or part of the I frames), which can be discarded based on the re-encoded data, or can also be discarded based on the original data;

[0168] The frame skipping processing described in the embodiments of the present application belongs to a subcategory of frame loss. Some data frames may be skipped as needed. The frame skipping may be uniform, i.e., skipping is performed at intervals of a preset number of data frames; or, the frame skipping may be uneven, i.e., skipping is performed at intervals of a random number of data frames.

[0169] In summary, the embodiments of the present application can perform data deletion by re-encoding, frame dropping, frame skipping and other processing methods according to the repeatability evaluation results and importance evaluation results of the video data, thereby compressing the storage space and preserving valuable historical data as much as possible.

[0170] In some embodiments, based on the repetitiveness evaluation result of the video data in the first period and / or the importance evaluation result of the video data in the first period, performing data deletion processing on the video data in the first period further includes:

[0171] When the repeatability evaluation result is less than a preset threshold, determine whether the event density in the event active area is greater than the preset threshold. If so, re-encode the video data in the event active area and discard the video data in the non-event active area; otherwise, perform frame skipping on the video data of the first time period.

[0172] That is to say, for event-active areas, the embodiments of the present application can encode and retain them separately, while discarding image data of other areas, thereby compressing storage space and preserving valuable historical data as much as possible, achieving selective data cleaning and increasing the retention time of important historical data.

[0173] In addition, it should be noted that, regarding the above three parameters, namely, the repeatability evaluation results, the importance evaluation results, and the event density in the event active area, data deletion can be performed by referring to one of the parameters alone, or by referring to multiple parameters. For example, see Fig. 9 , the three parameters of repeatability evaluation results, importance evaluation results, and event density in the event active area can be referred to simultaneously to perform data reduction processing on the current video data to be processed, and the details will not be repeated here.

[0174] The following is an introduction to the equipment or device provided in the embodiments of the present application, in which the explanations or examples of technical features that are the same or corresponding to those described in the above method will not be repeated later.

[0175] An electronic device provided in an embodiment of the present application, see Fig.10 , for example:

[0176] The processor 600 is used to read the program in the memory 620 and execute the following process:

[0177] Acquire video data of a first period of time collected for a target scene;

[0178] Based on the video data of the second time period corresponding to the target scene, performing repeatability evaluation on the video data of the first time period to obtain a repeatability evaluation result of the video data of the first time period; and performing importance evaluation on the video data of the first time period by performing event detection on the video data of the first time period to obtain an importance evaluation result of the video data of the first time period;

[0179] Based on the repeatability evaluation result of the video data of the first time period and / or the importance evaluation result of the video data of the first time period, data reduction processing is performed on the video data of the first time period.

[0180] In some embodiments, based on the video data of the second time period corresponding to the target scene, the video data of the first time period is evaluated for repeatability to obtain a repeatability evaluation result, including:

[0181] Compare the video data of the first time period with the video data of the second time period acquired for the same target scene to obtain at least one comparison result:

[0182] Based on the at least one comparison result, obtaining a repeatability evaluation result of the video data in the first time period;

[0183] The at least one comparison result includes one or a combination of the following parameters:

[0184] A similarity evaluation parameter between the image background in the video data of the first period and the image background in the video data of the second period;

[0185] A consistency evaluation parameter of a target in the video data of the first period of time and a target in the video data of the second period of time;

[0186] An evaluation parameter for the degree of similarity between the target type in the video data of the first period and the target type in the video data of the second period;

[0187] The degree to which the event type in the video data of the first time period is similar to the event type in the video data of the second time period is evaluated by a parameter.

[0188] In some embodiments, by detecting events in the video data of the first time period, performing importance evaluation on the video data of the first time period to obtain an importance evaluation result includes:

[0189] Performing event detection on the video data of the first time period to obtain at least one event;

[0190] Determining event content importance evaluation parameters of video data of the first time period based on the type and occurrence time period of the at least one event;

[0191] Determining, based on the occurrence area of ​​the at least one event, an area-based importance evaluation parameter of the video data of the first time period;

[0192] An importance evaluation result of the video data of the first time period is determined based on the event content importance evaluation parameter of the video data of the first time period and the region-based importance evaluation parameter of the video data of the first time period.

[0193] In some embodiments, determining the event content importance evaluation parameter of the video data of the first time period based on the type and occurrence time period of the at least one event includes:

[0194] Based on the type and occurrence period of the at least one event, the at least one event is divided into a plurality of groups of events; and for each group, based on the number and occurrence period of the events in the group, an event density of the group of events based on the time dimension is determined;

[0195] Determine the density of the overall events based on the time dimension based on the number and time period of all the events;

[0196] For each type, based on the number and occurrence period of events of this type, determine the density of events of this type based on the time dimension;

[0197] Based on the event density of each group of events based on the time dimension, the density of the overall events based on the time dimension, and the density of each type of events based on the time dimension, event content importance evaluation parameters of the video data of the first time period are determined.

[0198] In some embodiments, determining the region-based importance evaluation parameter of the video data of the first time period based on the occurrence region of the at least one event includes:

[0199] Based on the occurrence area of ​​the at least one event, determine the number of events in a preset key area in the picture and the number of events in a non-key area; based on the number of events in the key area and the area of ​​the key area, and the number of events in the non-key area and the area of ​​the non-key area, determine the overall event density based on the area;

[0200] Determine an event active region on the screen of the video data of the first time period, and determine the event density in the event active region based on the number of events in the event active region and the area of ​​the event active region;

[0201] Determine the ratio of the overlapping area between the key area and the event active area to the entire screen;

[0202] Based on the region-based density of the overall events, the event density within the event active region, and the ratio, a region-based importance evaluation parameter of the video data of the first time period is determined.

[0203] In some embodiments, based on the repetitiveness evaluation result of the video data in the first period and / or the importance evaluation result of the video data in the first period, performing data deletion processing on the video data in the first period includes:

[0204] When the repeatability evaluation result is greater than a preset threshold, performing frame skipping processing on the video data of the first time period;

[0205] When the importance evaluation result is greater than a preset threshold, re-encoding the video data of the first period according to preset encoding parameters;

[0206] When the importance evaluation result is less than a preset threshold, frame dropping processing is performed on the video data of the first time period.

[0207] In some embodiments, based on the repetitiveness evaluation result of the video data in the first period and / or the importance evaluation result of the video data in the first period, performing data deletion processing on the video data in the first period further includes:

[0208] When the repeatability evaluation result is less than a preset threshold, determine whether the event density in the event active area is greater than the preset threshold. If so, re-encode the video data in the event active area and discard the video data in the non-event active area; otherwise, perform frame skipping on the video data of the first time period.

[0209] The transceiver 610 is configured to receive and send data under the control of the processor 600 .

[0210] Among them, Fig.10In the embodiment, the bus architecture may include any number of interconnected buses and bridges, specifically one or more processors represented by processor 600 and various circuits of memory represented by memory 620 are linked together. The bus architecture may also link together various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. The bus interface provides an interface. The transceiver 610 may be a plurality of components, namely, a transmitter and a receiver, providing a unit for communicating with various other devices on a transmission medium, including wireless channels, wired channels, optical cables, and other transmission media. For different user devices, the user interface 630 may also be an interface capable of externally and internally connecting required devices, and the connected devices include but are not limited to a keypad, a display, a speaker, a microphone, a joystick, and the like.

[0211] The processor 600 is responsible for managing the bus architecture and general processing, and the memory 620 can store data used by the processor 600 when performing operations.

[0212] In some embodiments, the processor 600 may be a CPU (central processing unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array) or a CPLD (Complex Programmable Logic Device), and the processor may also adopt a multi-core architecture.

[0213] The processor calls the computer program stored in the memory to execute any of the methods provided in the embodiments of the present application according to the obtained executable instructions. The processor and the memory can also be arranged physically separately.

[0214] It should be noted here that the above-mentioned device provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned method embodiment, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as those in the method embodiment will not be described in detail here.

[0215] See also Fig.11 , a data deletion processing device provided in an embodiment of the present application includes:

[0216] The first unit 11 is used to obtain video data of a first period of time collected for a target scene;

[0217] The second unit 12 is used to perform repeatability evaluation on the video data of the first time period based on the video data of the second time period corresponding to the target scene, and obtain a repeatability evaluation result of the video data of the first time period; and to perform importance evaluation on the video data of the first time period by performing event detection on the video data of the first time period, and obtain an importance evaluation result of the video data of the first time period;

[0218] The third unit 13 is configured to perform data deletion processing on the video data of the first time period based on a repeatability evaluation result of the video data of the first time period and / or an importance evaluation result of the video data of the first time period.

[0219] In some embodiments, based on the video data of the second time period corresponding to the target scene, the video data of the first time period is evaluated for repeatability to obtain a repeatability evaluation result, including:

[0220] Compare the video data of the first time period with the video data of the second time period acquired for the same target scene to obtain at least one comparison result:

[0221] Based on the at least one comparison result, obtaining a repeatability evaluation result of the video data in the first time period;

[0222] The at least one comparison result includes one or a combination of the following parameters:

[0223] A similarity evaluation parameter between the image background in the video data of the first period and the image background in the video data of the second period;

[0224] A consistency evaluation parameter of a target in the video data of the first period of time and a target in the video data of the second period of time;

[0225] An evaluation parameter for the degree of similarity between the target type in the video data of the first period and the target type in the video data of the second period;

[0226] The degree to which the event type in the video data of the first time period is similar to the event type in the video data of the second time period is evaluated by a parameter.

[0227] In some embodiments, by detecting events in the video data of the first time period, performing importance evaluation on the video data of the first time period to obtain an importance evaluation result includes:

[0228] Performing event detection on the video data of the first time period to obtain at least one event;

[0229] Determining event content importance evaluation parameters of video data of the first time period based on the type and occurrence time period of the at least one event;

[0230] Determining, based on the occurrence area of ​​the at least one event, an area-based importance evaluation parameter of the video data of the first time period;

[0231] An importance evaluation result of the video data of the first time period is determined based on the event content importance evaluation parameter of the video data of the first time period and the region-based importance evaluation parameter of the video data of the first time period.

[0232] In some embodiments, determining the event content importance evaluation parameter of the video data of the first time period based on the type and occurrence time period of the at least one event includes:

[0233] Based on the type and occurrence period of the at least one event, the at least one event is divided into a plurality of groups of events; and for each group, based on the number and occurrence period of the events in the group, an event density of the group of events based on the time dimension is determined;

[0234] Determine the density of the overall events based on the time dimension based on the number and time period of all the events;

[0235] For each type, based on the number and occurrence period of events of this type, determine the density of events of this type based on the time dimension;

[0236] Based on the event density of each group of events based on the time dimension, the density of the overall events based on the time dimension, and the density of each type of events based on the time dimension, event content importance evaluation parameters of the video data of the first time period are determined.

[0237] In some embodiments, determining the region-based importance evaluation parameter of the video data of the first time period based on the occurrence region of the at least one event includes:

[0238] Based on the occurrence area of ​​the at least one event, determine the number of events in a preset key area in the picture and the number of events in a non-key area; based on the number of events in the key area and the area of ​​the key area, and the number of events in the non-key area and the area of ​​the non-key area, determine the overall event density based on the area;

[0239] Determine an event active region on the screen of the video data of the first time period, and determine the event density in the event active region based on the number of events in the event active region and the area of ​​the event active region;

[0240] Determine the ratio of the overlapping area between the key area and the event active area to the entire screen;

[0241] Based on the region-based density of the overall events, the event density within the event active region, and the ratio, a region-based importance evaluation parameter of the video data of the first time period is determined.

[0242] In some embodiments, based on the repetitiveness evaluation result of the video data in the first period and / or the importance evaluation result of the video data in the first period, performing data deletion processing on the video data in the first period includes:

[0243] When the repeatability evaluation result is greater than a preset threshold, performing frame skipping processing on the video data of the first time period;

[0244] When the importance evaluation result is greater than a preset threshold, re-encoding the video data of the first period according to preset encoding parameters;

[0245] When the importance evaluation result is less than a preset threshold, frame dropping processing is performed on the video data of the first time period.

[0246] In some embodiments, based on the repetitiveness evaluation result of the video data in the first period and / or the importance evaluation result of the video data in the first period, performing data deletion processing on the video data in the first period further includes:

[0247] When the repeatability evaluation result is less than a preset threshold, determine whether the event density in the event active area is greater than the preset threshold. If so, re-encode the video data in the event active area and discard the video data in the non-event active area; otherwise, perform frame skipping on the video data of the first time period.

[0248] It should be noted that the division of units in the embodiments of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional unit in each embodiment of the present application may be integrated into a processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0249] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (processor) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0250] Any of the devices or apparatuses provided in the embodiments of the present application may specifically be a desktop computer, a portable computer, a smart phone, a tablet computer, a personal digital assistant (PDA), etc. It may include a central processing unit (CPU), a memory, an input / output device, etc. The input device may include a keyboard, a mouse, a touch screen, etc. The output device may include a display device, such as a liquid crystal display (LCD), a cathode ray tube (CRT), etc.

[0251] The memory may include a read-only memory (ROM) and a random access memory (RAM), and provides the processor with program instructions and data stored in the memory. In an embodiment of the present application, the memory may be used to store the program of any of the methods provided in the embodiments of the present application.

[0252] The processor calls the program instructions stored in the memory, and the processor is used to execute any of the methods provided in the embodiments of the present application according to the obtained program instructions.

[0253] The present application embodiment also provides a computer program product or computer program, which includes a computer instruction, which is stored in a computer-readable storage medium. The processor of the computer device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction so that the computer device executes any of the methods described in the above embodiments. The program product can use any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, - but not limited to - an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of readable storage media (non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0254] The embodiment of the present application provides a computer-readable storage medium for storing computer program instructions used by the apparatus provided in the embodiment of the present application, which includes a program for executing any of the methods provided in the embodiment of the present application. The computer-readable storage medium may be a non-transitory computer-readable medium.

[0255] The computer-readable storage medium can be any available medium or data storage device that can be accessed by a computer, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CD, DVD, BD, HVD, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NANDFLASH), solid-state drive (SSD)), etc.

[0256] It should be understood that:

[0257] The access technology through which entities in the communication network transmit traffic can be any suitable current or future technology, such as WLAN (Wireless Local Access Network), WiMAX (Worldwide Interoperability for Microwave Access), LTE, LTE-A, 5G, Bluetooth, infrared, etc.; in addition, the embodiments can also apply wired technology, for example, IP-based access technology, such as a wired network or a fixed line.

[0258] Embodiments suitable for being implemented as software code or a portion thereof and running using a processor or processing functionality are independent of the software code and may be specified using any known or future developed programming language, such as a high-level programming language such as objective-C, C, C++, C#, Java, Python, Javascript, other scripting languages, etc., or a low-level programming language such as machine language or assembler.

[0259] The implementation of the embodiments is hardware independent and may be implemented using any known or future developed hardware technology or any mixture thereof, such as a microprocessor or CPU (central processing unit), MOS (metal oxide semiconductor), CMOS (complementary MOS), BiMOS (bipolar MOS), BiCMOS (bipolar CMOS), ECL (emitter coupled logic) and / or TTL (transistor-transistor logic).

[0260] Embodiments may be implemented as separate devices, apparatuses, units, components, or functions, or in a distributed manner, for example, one or more processors or processing functions may be used or shared in a process, or one or more processing segments or processing portions may be used and shared in a process, wherein one physical processor or more than one physical processor may be used to implement one or more processing portions dedicated to a specific process as described.

[0261] The device may be implemented by a semiconductor chip, a chipset, or a (hardware) module including such a chip or chipset.

[0262] The embodiments may also be implemented as any combination of hardware and software, such as ASIC (Application Specific IC (Integrated Circuit)) components, FPGA (Field Programmable Gate Array) or CPLD (Complex Programmable Logic Device) components or DSP (Digital Signal Processor) components.

[0263] The embodiments may also be implemented as a computer program product including a computer usable medium having computer readable program code embodied therein, the computer readable program code being adapted to perform the processes as described in the embodiments, wherein the computer usable medium may be a non-transitory medium.

[0264] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) that contain computer-usable program code.

[0265] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0266] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0267] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0268] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A data deletion processing method, characterized in that: The method comprises: Acquire video data of a first period of time collected for a target scene; Based on the video data of the second time period corresponding to the target scene, the video data of the first time period is evaluated for repeatability to obtain a repeatability evaluation result of the video data of the first time period; and the video data of the first time period is evaluated for importance by event detection of the video data of the first time period to obtain an importance evaluation result of the video data of the first time period; Based on the repeatability evaluation result of the video data of the first time period and / or the importance evaluation result of the video data of the first time period, data reduction processing is performed on the video data of the first time period.

2. The method according to claim 1, characterized in that Based on the video data of the second time period corresponding to the target scene, the video data of the first time period is evaluated for repeatability to obtain a repeatability evaluation result, including: Compare the video data of the first time period with the video data of the second time period acquired for the same target scene to obtain at least one comparison result: Based on the at least one comparison result, obtaining a repeatability evaluation result of the video data in the first time period; The at least one comparison result includes one or a combination of the following parameters: A similarity evaluation parameter between the image background in the video data of the first period and the image background in the video data of the second period; A consistency evaluation parameter of a target in the video data of the first period of time and a target in the video data of the second period of time; An evaluation parameter for the degree of similarity between the target type in the video data of the first period and the target type in the video data of the second period; The degree to which the event type in the video data of the first time period is similar to the event type in the video data of the second time period is evaluated by a parameter.

3. The method according to claim 1, characterized in that By detecting events in the video data of the first time period, importance evaluation is performed on the video data of the first time period to obtain an importance evaluation result, including: Performing event detection on the video data of the first time period to obtain at least one event; Determining event content importance evaluation parameters of video data of the first time period based on the type and occurrence time period of the at least one event; Determining, based on the occurrence area of ​​the at least one event, an area-based importance evaluation parameter of the video data of the first time period; An importance evaluation result of the video data of the first time period is determined based on the event content importance evaluation parameter of the video data of the first time period and the region-based importance evaluation parameter of the video data of the first time period.

4. The method according to claim 3, characterized in that Determining event content importance evaluation parameters of video data of the first time period based on the type and occurrence time period of the at least one event includes: Based on the type and occurrence period of the at least one event, the at least one event is divided into a plurality of groups of events; and, for each group, based on the number and occurrence period of the events in the group, an event density of the group of events based on the time dimension is determined; Determine the density of the overall events based on the time dimension based on the number and time period of all the events; For each type, based on the number and occurrence period of events of this type, determine the density of events of this type based on the time dimension; Based on the event density of each group of events based on the time dimension, the density of the overall events based on the time dimension, and the density of each type of events based on the time dimension, event content importance evaluation parameters of the video data of the first time period are determined.

5. The method according to claim 3, characterized in that: Determining, based on the occurrence area of ​​the at least one event, an area-based importance evaluation parameter of the video data of the first time period, comprising: Based on the occurrence area of ​​the at least one event, determine the number of events in a preset key area in the picture and the number of events in a non-key area; based on the number of events in the key area and the area of ​​the key area, and the number of events in the non-key area and the area of ​​the non-key area, determine the overall event density based on the area; Determine an event active region on the screen of the video data of the first time period, and determine the event density in the event active region based on the number of events in the event active region and the area of ​​the event active region; Determine the ratio of the overlapping area between the key area and the event active area to the entire screen; Based on the region-based density of the overall events, the event density within the event active region, and the ratio, a region-based importance evaluation parameter of the video data of the first time period is determined.

6. The method according to claim 1, characterized in that Based on the repetitiveness evaluation result of the video data of the first period and / or the importance evaluation result of the video data of the first period, performing data deletion processing on the video data of the first period includes: When the repeatability evaluation result is greater than a preset threshold, performing frame skipping processing on the video data of the first time period; When the importance evaluation result is greater than a preset threshold, re-encoding the video data of the first period according to preset encoding parameters; When the importance evaluation result is less than a preset threshold, frame dropping processing is performed on the video data of the first time period.

7. The method according to claim 6, characterized in that Based on the repetitiveness evaluation result of the video data of the first period and / or the importance evaluation result of the video data of the first period, performing data deletion processing on the video data of the first period, further comprising: When the repeatability evaluation result is less than a preset threshold, determine whether the event density in the event active area is greater than the preset threshold. If so, re-encode the video data in the event active area and discard the video data in the non-event active area; otherwise, perform frame skipping on the video data of the first time period.

8. A data processing device, characterized in that: The device comprises: The first unit is used to obtain video data of a first period of time collected for a target scene; The second unit is used to perform repeatability evaluation on the video data of the first time period based on the video data of the second time period corresponding to the target scene, and obtain a repeatability evaluation result of the video data of the first time period; and to perform importance evaluation on the video data of the first time period by performing event detection on the video data of the first time period, and obtain an importance evaluation result of the video data of the first time period; The third unit is used to perform data deletion processing on the video data of the first time period based on the repeatability evaluation result of the video data of the first time period and / or the importance evaluation result of the video data of the first time period.

9. An electronic device, characterized in that: include: A memory for storing program instructions; A processor, configured to call the program instructions stored in the memory, and execute the method according to any one of claims 1 to 7 according to the obtained program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable the computer to execute the method according to any one of claims 1 to 7.

Images