Video coverage method, electronic terminal and computer readable storage medium

Abstract

The invention provides a video coverage method, an electronic terminal and a computer readable storage medium. The video coverage method comprises the following steps: calculating a weight corresponding to each video fragment based on attribute information corresponding to the video fragment; the attribute information corresponding to the video fragment comprises at least one of time information of the video fragment, state information of video equipment corresponding to the video fragment and event state information corresponding to the video fragment; and covering the video fragments based on the weight corresponding to each video fragment. Therefore, the state of the video recording equipment can be associated with the event of the video clip, and important videos are prevented from being lost when video coverage is carried out.

Description

Technical Field

[0001] This application relates to the field of video recording technology, and in particular to a video recording overlay method, an electronic terminal, and a computer-readable storage medium. Background Technology

[0002] Existing low-power AOV (Always On Video) cameras often record continuously in outdoor environments without electricity or network access. The traditional method of video overwriting is to set a fixed priority for regular video recordings, and when overwriting, regular video recordings will be overwritten first, but some very important video clips may be lost. Summary of the Invention

[0003] The main technical problem addressed by this application is to provide a video recording overlay method, apparatus, electronic terminal, and computer-readable storage medium to solve the problem of important video recording loss in the prior art.

[0004] To solve the above-mentioned technical problems, the first technical solution adopted in this application is: to provide a video overlay method, including: The weight of each video segment is calculated based on the attribute information corresponding to the video segment; the attribute information corresponding to the video segment includes at least one of the following: the time information of the video segment, the status information of the recording device corresponding to the video segment, and the event status information corresponding to the video segment. The video segments are covered based on the weight corresponding to each video segment.

[0005] In one embodiment, calculating the weight corresponding to each video segment based on the attribute information corresponding to the video segment includes: Based on the attribute information corresponding to the video segment, the reference weight corresponding to each video segment is determined from the preset weight table. The reference weight includes at least one of time weight, state weight, and event weight. The weight corresponding to each video segment is calculated based on the reference weight.

[0006] In one embodiment, determining the reference weight corresponding to each video segment from a preset weight table based on the attribute information corresponding to the video segment includes: The event weight of a video segment is determined from a preset weight table based on the event status information corresponding to the video segment; wherein, the event status information includes event information and / or the status information of the recording device; The preset weight table includes: various preset event status information of the recording device, and the preset event weight corresponding to each preset event status information; wherein, the preset event weight is positively correlated with the importance of the preset event status information.

[0007] In one embodiment, determining the reference weight corresponding to each video segment from a preset weight table based on the attribute information corresponding to the video segment includes: The time decay coefficient is determined from a preset weight table based on the event status information corresponding to the video clip; The time weight of each video segment is determined based on the time information and time decay coefficient corresponding to the video segment. The preset weight table includes: various preset event status information of the recording device, and a preset time decay coefficient corresponding to each preset event status information; the preset time decay coefficient is positively correlated with the importance of the preset event status information.

[0008] In one embodiment, determining the reference weight corresponding to each video segment from a preset weight table based on the attribute information corresponding to the video segment includes: The state weight of a video segment is determined from a preset weight table based on the state information of the recording device corresponding to the video segment. The preset weight table includes: various preset state information of the recording device, and the preset state weight corresponding to each preset state information; among them, the preset state weight is positively correlated with the attention of the preset state information.

[0009] In one embodiment, the time weight corresponding to the video segment is negatively correlated with the time decay coefficient.

[0010] In one embodiment, calculating the weight corresponding to each video segment based on reference weights includes: The weight of each video segment is obtained by calculating the product of the time weight, the state weight, and the time weight.

[0011] In one embodiment, covering video segments based on the weight corresponding to each video segment includes: In response to coverage conditions, delete video clips with weights less than a preset value; or In response to coverage conditions, a preset number of video clips with low weights are deleted.

[0012] To solve the above-mentioned technical problems, the second technical solution adopted in this application is: to provide an electronic terminal, which includes a memory and a processor coupled to each other, the processor being used to execute program instructions stored in the memory, and the processor being used to execute program data to implement the steps in the video recording overlay method described above.

[0013] To solve the above-mentioned technical problems, the third technical solution adopted in this application is: to provide a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, to implement the steps in the video recording overlay method described above.

[0014] The beneficial effects of this application are as follows: Unlike existing technologies, the video overlay method provided in this application includes calculating the weight of each video segment based on the attribute information corresponding to the video segment; the attribute information corresponding to the video segment includes at least one of: the time information of the video segment, the status information of the recording device corresponding to the video segment, and the event status information corresponding to the video segment; and overlaying the video segments based on the weight corresponding to each video segment. In this way, the status of the recording device and the events of the video segments can be associated, avoiding the loss of important recordings during video overlay. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating the first embodiment of the video overlay method provided in this application; Figure 2 yes Figure 1 A flowchart illustrating an embodiment of step S11; Figure 3 This is a schematic diagram of the framework of an embodiment of the electronic terminal provided in this application; Figure 4 This is a schematic diagram of a framework of an embodiment of the computer-readable storage medium provided in this application. Detailed Implementation

[0017] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0018] In the following description, specific details such as particular system architectures, interfaces, and technologies are presented for illustrative purposes rather than for limiting purposes, in order to provide a thorough understanding of this application.

[0019] In this article, the term "and / or" simply describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / " generally indicates that the preceding and following related objects have an "or" relationship. Furthermore, "more" in this article means two or more objects.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0021] Before providing a further detailed description of the embodiments of this application, the nouns and terms involved in the embodiments of this application will be explained, and the nouns and terms involved in the embodiments of this application shall be interpreted as follows.

[0022] The video overlay method provided in this application can be implemented by a server or terminal alone, or by a server and terminal working together. In some embodiments, the terminal or server can implement the video overlay method provided in this application by running a computer program. For example, the computer program can be a native program or software module in an operating system; it can be a native application (APP), i.e., a program that needs to be installed in the operating system to run, such as a client that supports virtual scenes, such as a game APP; it can also be a mini-program, i.e., a program that only needs to be downloaded to a browser environment to run; or it can be a mini-program that can be embedded in any APP. In short, the above-mentioned computer program can be any form of application, module, or plugin.

[0023] To enable those skilled in the art to better understand the technical solution of this application, a video overlay method provided by this application will be described in further detail below with reference to the accompanying drawings and specific embodiments.

[0024] Please see Figure 1 The above is a flowchart illustrating the first embodiment of the video recording overlay method of this application, specifically including: Step S11: Calculate the weight of each video segment based on the attribute information corresponding to the video segment; the attribute information corresponding to the video segment includes at least one of the following: the time information of the video segment, the status information of the recording device corresponding to the video segment, and the event status information corresponding to the video segment.

[0025] In one embodiment, the attribute information corresponding to a video segment includes the time information of the video segment. It is understood that the longer the time of the video segment relative to the current time, the older and less important the video segment is. When overwriting video clips, a weight is calculated for each video segment based on its time information. Based on this weight, video clips with higher weights, such as newer segments in the time chain, can be preferentially retained. It should be noted that the time information of a video segment includes at least one of the time the video segment was recorded, the time the video segment finished recording, and the duration of the video segment.

[0026] In another embodiment, the attribute information corresponding to the video segment includes the status information of the recording device corresponding to the video segment. It is understood that AOV cameras, in addition to recording important events, also need to monitor the device status during recording. When overlaying video clips, a weight is calculated for each video segment based on the status information of the recording device corresponding to the segment. Based on this weight, video clips with higher weights, such as those experiencing device malfunctions, can be preferentially retained. It should be noted that the status information of the recording device includes, for example, sleep mode, wake-up mode, offline mode, low battery mode, etc.

[0027] In another embodiment, the attribute information corresponding to the video segment includes the event status information corresponding to the video segment. It should be noted that the event status information corresponding to the video segment includes event information and the status information of the recording device. Event information includes, for example, SMD (Smart Motion Detection) recording, MD (Motion Detection) recording, tamper-proof recording, regular recording, etc. The status information of the recording device corresponding to the video segment includes states such as sleep mode, wake-up mode, offline mode, low battery mode, etc. It is understandable that for AOV cameras, SMD (Smart Motion Detection) recording, MD (Motion Detection) recording, and tamper-proof recording are generally considered important recordings, while regular recordings are considered less important. The status information of the recording device is also a target that needs attention.

[0028] When overlaying video recordings, the weight of each video recording segment is calculated based on the event status information corresponding to the video segment. When overlaying video recordings based on this weight, important video recording segments with higher weights, such as SMD (Smart Motion Detection), MD (Motion Detection) video recordings, and tamper-proof video recordings, can be retained first.

[0029] Of course, in other embodiments, the attribute information corresponding to the video segment may also include any two of the following: the time information of the video segment, the status information of the recording device corresponding to the video segment, and the event status information corresponding to the video segment.

[0030] In one specific embodiment, the attribute information corresponding to the video segment may further include: the time information of the video segment, the status information of the recording device corresponding to the video segment, and the event status information corresponding to the video segment. This application will use this as an example for illustration.

[0031] Combination Figure 2 Step S11 includes: Step S21: Determine the reference weight corresponding to each video segment from the preset weight table based on the attribute information corresponding to the video segment. The reference weight includes at least one of time weight, state weight, and event weight.

[0032] Understandably, time weights can be determined based on the time information of the video clip; state weights can be determined based on the state information of the recording device corresponding to the video clip; and event weights can be determined based on the event state information corresponding to the video clip.

[0033] As mentioned above, assuming the attribute information corresponding to a video clip includes: the time information of the video clip, the status information of the recording device corresponding to the video clip, and the event status information corresponding to the video clip, then the time weight is determined based on the time information of the video clip, the status weight is determined based on the status information of the recording device corresponding to the video clip, and the event weight is determined based on the event status information corresponding to the video clip.

[0034] In one embodiment, determining the event weight based on the event status information corresponding to the video segment includes: determining the event weight of the video segment from a preset weight table based on the event status information corresponding to the video segment; the preset weight table includes: various preset event status information of the recording device, and a preset event weight corresponding to each preset event status information.

[0035] Based on this, the pre-set weight table is designed as shown in Table (1) below:

[0036] Table (1) The preset event weights are positively correlated with the importance of the preset event status information. Understandably, the event status information corresponding to a video clip includes event information and / or the status information of the recording device. Event information includes, for example, SMD (Smart Motion Detection) recording, MD (Motion Detection) recording, tamper-proof recording, and regular recording; the recording device status information includes, for example, sleep mode, wake-up mode, offline mode, and low battery mode. Understandably, for AOV cameras, SMD (Smart Motion Detection), MD (Motion Detection), and tamper-proof recordings are generally considered important, while regular recordings are considered less important. The status information of the recording device is also a target that needs attention. Therefore, in the preset weight table, SMD (Smart Motion Detection), MD (Motion Detection), and tamper-proof recordings are given the highest weight, followed by the status information of the recording device, and regular recordings have the lowest weight.

[0037] Thus, assuming that the reference weights corresponding to the video clips only include event weights, the corresponding event weights can be determined from the above table (1) based on the event status information corresponding to the video clips.

[0038] For example, in scenario 1: the time status information corresponding to video segment a is: the recording device is offline / sleep wake-up / power on / off, but no SMD, MD, or anti-tamper events have occurred, then the event weight P is determined to be 2.

[0039] Scenario 2: The time status information corresponding to video clip b is: the recording device is offline / sleep wake-up / power on / off, but an SMD / MD / tamper event has occurred. Since the SMD / MD / tamper event is an important event, the event weight is determined to be P=3.

[0040] Scenario 3: The time status information corresponding to video segment c is: the recording device is not offline / sleep wake-up / power on / off, and no SMD / MD / tamper events have occurred. Therefore, it can be determined that the recording device is in normal recording state, and the event weight P is determined to be 1.

[0041] In one embodiment, determining the time weight based on the time information of the video segment includes: determining a time decay coefficient from a preset weight table based on the event status information corresponding to the video segment; and determining the time weight corresponding to each video segment based on the time information and the time decay coefficient. The preset weight table includes: various preset event status information of the recording device, and a preset time decay coefficient corresponding to each preset event status information; the preset time decay coefficient is positively correlated with the importance of the preset event status information.

[0042] Specifically, the preset weight table is shown in Table (2) below:

[0043] Table (2) Specifically, the preset weight table shown in Table (2) differs from the preset weight table shown in Table (1) in that it also includes various preset event status information of the recording device, as well as the preset time decay coefficient corresponding to each preset event status information. Among them, the preset time decay coefficient is positively correlated with the importance of the preset event status information. That is, the more important the preset event status information, the larger the preset time decay coefficient.

[0044] For AOV cameras, SMD (Intelligent Motion Detection) recording, MD (Motion Detection) recording, and tamper-proof recording are generally considered important recordings, so their corresponding preset time decay coefficient is set to the maximum, such as 0.3. Regular recordings are considered unimportant recordings, so their corresponding preset time decay coefficient is set to a smaller value, such as 0.1. The status information of the recording device is also a target that needs attention, so its corresponding preset time decay coefficient is set to a larger value, such as 0.2.

[0045] After determining the time decay coefficient corresponding to the video segment, the time weight corresponding to each video segment is further determined based on the time information and time decay coefficient corresponding to the video segment.

[0046] In one embodiment, the time weight corresponding to a video segment is negatively correlated with the time decay coefficient. In a specific embodiment, the time weight is denoted as T, where T = (1 / (1+α * Δt)). Here, α represents the time decay coefficient, and Δt represents the time information corresponding to the video segment, specifically the time difference between the recording time of the video segment and the current time. In this embodiment, a larger time decay coefficient results in a smaller time weight, indicating a more significant impact of the time difference on the time weight; conversely, a smaller time decay coefficient results in a larger time weight, indicating a smaller impact of the time difference on the time weight. It can be understood that if Δt is larger, it indicates that the video segment is further removed from the current time, thus the time weight T is smaller, and its importance is lower.

[0047] For example, in scenario 1: the time status information corresponding to video segment a is: the recording device is offline / sleep wake-up / power on / off, but no SMD, MD, or anti-tamper events have occurred. At this time, the event weight P is determined to be 2, the time decay coefficient α is 0.2, and the time difference between the video segment and the current time Δt is 1h. Then the time weight T is (1 / (1+0.2 * 1)=0.83).

[0048] Scenario 2: The time status information corresponding to video clip b is: the recording device is offline / sleep wake-up / power on / off, but an SMD / MD / tamper event has occurred. Since the SMD / MD / tamper event is an important event, the event weight P=3 and the time decay coefficient α=0.3 are determined; and the time difference between the video clip and the current time Δt=1h, then the time weight T=(1 / (1+0.3*1)=0.77.

[0049] Scenario 3: The time status information corresponding to the recording segment c is as follows: the recording device is not offline / sleep wake-up / power on / off, and no SMD / MD / tamper events have occurred. Therefore, it can be determined that the recording device is in a normal recording state. At this time, the event weight P=1 and the time decay coefficient α=0.1 are determined. The time difference between the recording segment and the current time Δt=1h, so the time weight T=(1 / (1+0.1 * 1)=0.9.

[0050] It should be noted that during the recording of a video segment, the device's state information may change. In this embodiment, the weight of the video segment is dynamically adjusted based on these state changes. Specifically, the state weight of the video segment is determined from a preset weight table based on the state information of the recording device corresponding to that segment. The preset weight table includes various preset state information of the recording device and a preset state weight corresponding to each preset state information.

[0051] In this embodiment, the preset weight table is shown in Table (3) below:

[0052] Table (3) It should be noted that the preset state weight is positively correlated with the level of attention paid to the preset state information. Specifically, if the user is more concerned about the offline state, the weight of the offline state can be set to the highest; if the user is more concerned about the power on / off state, the weight of the power on / off state can be set to the highest. There is no specific limitation; this embodiment uses the offline state as the example with the highest weight for explanation.

[0053] Thus, assuming that the reference weights corresponding to the video segment include event weights, time weights, and state weights, the corresponding event weights and time decay coefficients can be determined from the above table (2) based on the event state information corresponding to the video segment, and the state weights can be determined from the above table (3). The product of the time weights, state weights, and time weights is calculated to obtain the weights corresponding to each video segment.

[0054] For example, in scenario 1: the time status information corresponding to video clip a is: the recording device is offline / sleep wake-up / power on / off (event weight P=2); and the recording device is currently offline (state weight S=2.0); no SMD, MD, or tamper events occurred in video clip a, the time decay coefficient α=0.2, and the time difference between the video clip and the current time Δt=1h, then the time weight T=(1 / (1+0.2 * 1)=0.83.

[0055] Scenario 2: The time status information corresponding to video clip b is as follows: the recording device is offline / sleep wake-up / power on / off (event weight P=2); and the recording device is in sleep state at the current time (state weight S=1.2); no SMD, MD, or anti-tamper events occurred in video clip b, the time decay coefficient α=0.2, and the time difference between the video clip and the current time Δt=1h, then the time weight T=(1 / (1+0.2 * 1)=0.83.

[0056] Scenario 3: The time status information corresponding to video segment c is: the recording device is offline / sleep wake-up / power on / off (event weight P=2); and the recording device is currently in sleep state (state weight S=1.2); video segment b has SMD, MD, and tamper events. Since the importance of SMD, MD, and tamper events is higher than offline / sleep wake-up / power on / off, the event weight is determined to be P=3, the time decay coefficient α=0.3, and the time difference between the video segment and the current time Δt=1h. Therefore, the time weight T=(1 / (1+0.3 * 1)=0.77).

[0057] Step S22: Calculate the weight corresponding to each video segment based on the reference weight.

[0058] Specifically, the product of time weight, state weight, and time weight is calculated to obtain the weight corresponding to each video segment.

[0059] Let W denote the weight of the video segment, then W = P × T × S. Where P represents the event weight of the video segment, T represents the time weight of the video segment, and S represents the state weight of the video segment.

[0060] For example, in scenario 1: the time status information corresponding to video clip a is: the recording device is offline / sleep / wake-up / power on / off (event weight P=2); and the recording device is currently offline (state weight S=2.0); video clip a has not experienced SMD, MD, or tamper events, the time decay coefficient α=0.2, and the time difference between video clip a and the current time Δt=1h. Therefore, the time weight T=(1 / (1+0.2 * 1)=0.83). Based on the event weight (P=2), state weight (S=2.0), and time weight (T=0.83), the weight W corresponding to video clip a is calculated as W=P×T×S=2×0.83×2=3.32.

[0061] Scenario 2: The time status information corresponding to video clip b is as follows: the recording device is offline / sleep / wake-up / power on / off (event weight P=2); and the recording device is currently in sleep mode (state weight S=1.2); no SMD, MD, or tamper events occurred in video clip b, the time decay coefficient α=0.2, and the time difference between video clip b and the current time Δt=1h. Therefore, the time weight T=(1 / (1+0.2 * 1)=0.83. Based on the event weight (P=2), state weight (S=1.2), and time weight (T=0.83), the weight corresponding to video clip b is calculated as W=P×T×S=2×0.83×1.2=1.99.

[0062] Scenario 3: The time status information corresponding to video segment c is as follows: the recording device is offline / sleep wake-up / power on / off (event weight P=2); and the recording device is currently in sleep mode (state weight S=1.2); video segment c experiences SMD, MD, and tamper events. Since the importance of SMD, MD, and tamper events is higher than offline / sleep wake-up / power on / off events, the event weight is determined to be P=3, the time decay coefficient α=0.3, and the time difference between video segment c and the current time Δt=1h. Therefore, the time weight T=(1 / (1+0.3 * 1)=0.77). Based on the event weight (P=3), state weight (S=1.2), and time weight (T=0.77), the weight corresponding to video segment c is calculated as W=P×T×S=3×0.77×1.2=2.77.

[0063] Step S12: Cover the video segments based on the weight corresponding to each video segment.

[0064] It's important to note that overwriting video clips actually involves deleting a portion of the footage when preset conditions are met. For example, if storage capacity is insufficient, some clips need to be deleted to free up space for new clips. To avoid impacting subsequent video playback, less important clips are generally deleted first, while retaining as many important clips as possible.

[0065] In one specific embodiment, in response to a coverage condition, video clips with weights less than a preset value are deleted; or, in response to a coverage condition, a preset number of video clips with small weights are deleted. A coverage condition may be, for example, insufficient storage space in the memory, such as insufficient remaining storage space to store one video clip, or, for example, the remaining storage space has not reached a preset storage space. In one embodiment, a preset weight value can be set, and video clips with weights less than the preset value are deleted. In another embodiment, the weights can be sorted from largest to smallest, and a preset number of video clips with smaller weights are deleted, thereby completing the video coverage.

[0066] It should be noted that when deleting a video clip, the entire clip should be deleted to avoid data residue.

[0067] Specifically, the weight corresponding to each video segment can be calculated through the above process. It's understandable that as time changes, the time difference Δt between the video segment and the current time changes, the time weight changes, and consequently, the weight of the corresponding video segment changes. Under the same conditions (i.e., device status and event status information), the longer the video segment, the smaller the calculated weight, and the higher the priority for deletion during overwriting. When there are abnormal device statuses such as offline / sleep / wake-up / power on / off, the longer the recording time, the more significant the influence of the status weight on the calculated weight, and the lower the priority for deletion during overwriting. Similarly, when event status information such as SMD, MD, or tamper-proof events occur, the longer the recording event, the more significant the influence of the event weight on the calculated weight, and the lower the priority for deletion during overwriting.

[0068] This application's video overlay method associates and combines the recording device's status, the events corresponding to the recording segments, and the events corresponding to the recording segments. Based on the correlation between device status switching (sleep, wake-up, offline, low battery) and business triggers (SMD events, anti-tamper events), it achieves deep binding between the overlay strategy and the device's operating logic, ensuring that truly important recordings associated with the device status are preserved to the maximum extent. By introducing a time decay coefficient, it addresses the problem of accidental deletion of important data. This application's method considers the correlation between device status and business events, preventing the loss of critical recordings during overlay.

[0069] Please see Figure 3 , Figure 3This is a schematic diagram of the framework of an embodiment of the electronic terminal provided in this application. The electronic terminal 80 includes a memory 81 and a processor 82 coupled to each other. The processor 82 is used to execute program instructions stored in the memory 81 to implement the steps of any of the above-described video recording overlay method embodiments. In a specific implementation scenario, the terminal 80 may include, but is not limited to, a microcomputer, a server, etc. In addition, the terminal 80 may also include mobile devices such as laptops and tablets, which are not limited here.

[0070] Specifically, processor 82 controls itself and memory 81 to implement the steps of any of the above-described video overlay method embodiments. Processor 82 may also be referred to as a CPU (Central Processing Unit). Processor 82 may be an integrated circuit chip with signal processing capabilities. Processor 82 may also be a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component. A general-purpose processor may be a microprocessor or any conventional processor. Furthermore, processor 82 may be implemented using integrated circuit chips.

[0071] Please see Figure 4 , Figure 4 This is a schematic diagram of a framework of an embodiment of the computer-readable storage medium provided in this application. The computer-readable storage medium 90 stores program instructions 901 that can be executed by a processor. The program instructions 901 are used to implement the steps of any of the above-described video overlay method embodiments.

[0072] In some embodiments, the functions or modules of the apparatus provided in this disclosure can be used to perform the methods described in the above method embodiments. The specific implementation can be referred to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0073] The description of the various embodiments above tends to emphasize the differences between the various embodiments. The similarities or similarities between them can be referred to, and for the sake of brevity, they will not be repeated here.

[0074] In the several embodiments provided in this application, it should be understood that the disclosed methods and apparatus can be implemented in other ways. For example, the apparatus implementations described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0075] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0076] If the integrated unit is implemented as 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 this application, in essence, 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. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods of various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0077] The above are merely embodiments of this application and do not limit the scope of patent protection of this application. Any equivalent structural or procedural changes made using the content of this application’s specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of this application.

Claims

1. A video recording overlay method, characterized in that, include: The weight of each video segment is calculated based on the attribute information corresponding to the video segment. The attribute information corresponding to the video clip includes at least one of the following: the time information of the video clip, the status information of the recording device corresponding to the video clip, and the event status information corresponding to the video clip; The video segments are covered based on the weight corresponding to each video segment.

2. The video recording overlay method according to claim 1, characterized in that, Calculate the weight of each video segment based on the attribute information corresponding to the video segment, including: Based on the attribute information corresponding to the video segment, a reference weight corresponding to each video segment is determined from a preset weight table. The reference weight includes at least one of time weight, state weight, and event weight. The weight corresponding to each video segment is calculated based on the reference weight.

3. The video recording overlay method according to claim 2, characterized in that, Based on the attribute information corresponding to the video segments, a reference weight is determined from a preset weight table, including: The event weight of the video segment is determined from the preset weight table based on the event status information corresponding to the video segment; wherein, the event status information includes event information and / or the status information of the recording device; The preset weight table includes: various preset event state information of the recording device, and a preset event weight corresponding to each preset event state information; wherein, the preset event weight is positively correlated with the importance of the preset event state information.

4. The video recording overlay method according to claim 2, characterized in that, Based on the attribute information corresponding to the video segment, a reference weight is determined from a preset weight table, including: The time decay coefficient is determined from the preset weight table based on the event status information corresponding to the video segment; The time weight of each video segment is determined based on the time information corresponding to the video segment and the time decay coefficient. The preset weight table includes: various preset event status information of the recording device, and a preset time decay coefficient corresponding to each preset event status information; the preset time decay coefficient is positively correlated with the importance of the preset event status information.

5. The video recording overlay method according to claim 2, characterized in that, Based on the attribute information corresponding to the video segments, a reference weight is determined from a preset weight table, including: The state weight of the video segment is determined from the preset weight table based on the state information of the recording device corresponding to the video segment. The preset weight table includes: various preset state information of the recording device, and a preset state weight corresponding to each preset state information; wherein, the preset state weight is positively correlated with the attention level of the preset state information.

6. The video recording overlay method according to claim 5, characterized in that, The time weight corresponding to the video segment is negatively correlated with the time decay coefficient.

7. The video recording overlay method according to claim 2, characterized in that, Calculating the weight corresponding to each video segment based on the reference weight includes: The weight corresponding to each video segment is obtained by calculating the product of the time weight, the state weight, and the time weight.

8. The video recording overlay method according to any one of claims 1 to 7, characterized in that, The video segments are covered based on the weight corresponding to each video segment, including: In response to coverage conditions, delete video clips with weights less than a preset value; or In response to coverage conditions, a preset number of video clips with low weights are deleted.

9. An electronic terminal, characterized in that, The electronic terminal includes a memory and a processor coupled to each other. The processor is used to execute program instructions stored in the memory and to execute program data to implement the steps in the video overlay method as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the video overlay method as described in any one of claims 1 to 8.

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