CN111314776B - Fragmentation acceleration method for discontinuous storage video - Google Patents
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- CN111314776B CN111314776B CN201911177764.7A CN201911177764A CN111314776B CN 111314776 B CN111314776 B CN 111314776B CN 201911177764 A CN201911177764 A CN 201911177764A CN 111314776 B CN111314776 B CN 111314776B
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- 239000012634 fragment Substances 0.000 claims abstract description 45
- 238000012545 processing Methods 0.000 claims abstract description 26
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/44—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
- H04N21/44008—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs involving operations for analysing video streams, e.g. detecting features or characteristics in the video stream
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/80—Generation or processing of content or additional data by content creator independently of the distribution process; Content per se
- H04N21/83—Generation or processing of protective or descriptive data associated with content; Content structuring
- H04N21/845—Structuring of content, e.g. decomposing content into time segments
- H04N21/8456—Structuring of content, e.g. decomposing content into time segments by decomposing the content in the time domain, e.g. in time segments
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/76—Television signal recording
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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Abstract
The invention provides a fragmentation acceleration method aiming at discontinuous storage video, which comprises the steps of collecting video segments to be processed and carrying out fragmentation processing on the video segments to be processed, wherein the fragmentation processing comprises the following steps: acquiring the maximum fragment number of a video segment to be processed according to the minimum fragment time and the time of each video segment; calculating the proportion of the maximum fragment number of each video segment to the maximum fragment number of the video segment to be processed; acquiring the number of newly added segments of each corresponding video segment according to the proportion; the invention can meet the requirements of the optimization use of resources and the improvement of the analysis rate under the condition that video discontinuous storage exists in a system with limited GPU analysis resources aiming at the tasks of video record analysis.
Description
Technical Field
The invention relates to the field of computer application, in particular to a fragmentation acceleration method aiming at discontinuous storage video.
Background
Video monitoring is an important component of a security system, and in recent years, through evolution of algorithms and technological innovation, a video analysis technology is applied to the security industry on a large scale. The video record in the storage server is analyzed through an algorithm, important information such as people, vehicles and things is extracted, and the information is further converted into information used by relevant functional departments, so that the conversion of video data into information and information is realized.
However, certain analysis resources are required to be occupied for video analysis, and under the condition of limited resources, reasonable fragment cutting and parallel analysis are carried out on video records, so that the video analysis speed can be improved. Therefore, when the situation that video recording in the storage server is discontinuous is faced, how to cut the video recording fragments to realize reasonable utilization of resources is a problem which needs to be solved urgently at present.
Disclosure of Invention
In view of the above-mentioned shortcomings of the prior art, the present invention provides a fragmentation acceleration method for discontinuous storage of video to solve the above-mentioned technical problems.
The invention provides a fragmentation acceleration method aiming at discontinuous storage video, which comprises the following steps
The method comprises the following steps of collecting video segments to be processed, and carrying out fragmentation processing on the video segments to be processed, wherein the fragmentation processing comprises the following steps:
acquiring the maximum fragment number of a video segment to be processed according to the minimum fragment time and the time of each video segment;
calculating the proportion of the maximum fragment number of each video segment to the maximum fragment number of the video segment to be processed;
and acquiring the number of newly added slices of each corresponding video segment according to the proportion.
Optionally, resource allocation and video analysis are performed according to the fragmentation processing result and the remaining available analysis resources, when a fragmentation analysis is completed and the analysis resources are vacated, secondary fragmentation processing is performed on the video segments after fragmentation processing, and video analysis is performed on the video segments after secondary fragmentation processing by reallocating resources.
Optionally, when a fragment analysis completes and vacates an analysis resource, a new initial analysis time of another fragment is obtained, and secondary fragment processing is performed according to the new initial analysis time of the other fragment.
Optionally, the new starting analysis time of the other fragments is obtained according to the original starting time and the original ending time of the other fragments and the analysis progress of the fragment.
Optionally, the starting analysis time of the other slices is obtained by the following formula:
ts′＝ts+(ts-te)×p
wherein ts' is a new initial analysis time of other segments, ts is a start time of a video segment to be processed, te represents an end time of the video segment, and p is an analysis progress of the video segment.
Optionally, the number of the fragments that need to be newly added to each current video segment is respectively obtained according to the number of the remaining analysis resources at the current time and the number of the actual video segments stored at the current time, so as to obtain the number of the final fragments of the whole video segment.
Optionally, the number of segments to be newly added to each corresponding video segment is obtained through the following formula:
EA is the residual analysis resource at a certain moment, N is the number of actual video segments stored in a time period, Tn is the duration of the nth video segment, tmin is the minimum duration capable of being fragmented, and M is the number of finally obtained fragments.
Optionally, a maximum abnormal time threshold is obtained according to the fragmentation processing result, and when the cumulative abnormal time of the logic fragmentation task exceeds the maximum abnormal time threshold, the allocated resources are released and the video task state is updated from the running state to the abnormal state.
Optionally, a waiting time threshold is preset, and when the allocated resources are released and the video recording task state is updated from the running state to the abnormal state, the resources are reallocated to try analysis when the waiting time threshold is reached.
The invention also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the method of any one of the preceding claims.
The present invention also provides an electronic terminal, comprising: a processor and a memory;
the memory is adapted to store a computer program and the processor is adapted to execute the computer program stored by the memory to cause the terminal to perform the method as defined in any one of the above.
The invention has the beneficial effects that: the invention aims at the fragmentation acceleration method for discontinuous storage of video, can meet the requirements of optimizing use of resources and improving the analysis rate under the condition that the video is discontinuous in storage aiming at the task of video analysis in a system with limited GPU analysis resources.
Drawings
Fig. 1 is a flowchart illustrating a fragmentation acceleration method for discontinuous storage video according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a fragmentation result according to a first embodiment of a fragmentation acceleration method for discontinuous storage video recording in an embodiment of the present invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.
In the following description, numerous details are set forth to provide a more thorough explanation of embodiments of the present invention, however, it will be apparent to one skilled in the art that embodiments of the present invention may be practiced without these specific details, and in other embodiments, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring embodiments of the present invention.
As shown in fig. 1, the fragmentation acceleration method for discontinuous storage of video recording in this embodiment includes
The method comprises the following steps of collecting video segments to be processed, and carrying out fragmentation processing on the video segments to be processed, wherein the fragmentation processing comprises the following steps:
acquiring the maximum fragment number of a video segment to be processed according to the minimum fragment time and the time of each video segment;
calculating the proportion of the maximum fragment number of each video segment to the maximum fragment number of the video segment to be processed;
and acquiring the number of newly added slices of each corresponding video segment according to the proportion.
In the embodiment, the fragmentation acceleration method for discontinuous storage video is based on a scene that a user needs to analyze the storage video within a certain period of time, because in the whole analysis system, analysis resources are limited at a moment, when a plurality of segments of videos exist due to discontinuous video storage within a video time period, the videos stored within the whole time period need to be analyzed, but the videos are not continuous in an actual situation.
In this embodiment, resource allocation and video analysis are performed according to the result of fragmentation processing and the remaining available analysis resources, and when a fragmentation analysis is completed and analysis resources are vacated, secondary fragmentation processing is performed on the video segments after fragmentation processing, and video analysis is performed on the video segments after secondary fragmentation processing by reallocating resources.
First, the maximum number of slices P that can be obtained in a stored video segment is calculated by the following formula.
Wherein, TnIndicating the duration of the video segment of the nth segment, tminIndicating the minimum time duration, T, that can be slicedn/tminThe maximum number of slices which can be achieved by a segment of video is shown, and the maximum number of slices P which can be obtained theoretically by a segment of video is deduced after summation.
Then pass through
The final number of slices M is calculated,
where EA is the remaining analysis resources at a certain time, N is the number of actual video segments stored in a time period, and T isnFor the duration of the video segment of the nth segment, tminM is the number of fragments finally obtained, and is the minimum time length for which fragmentation can be performed.
And then, partitioning according to the formula, and starting to allocate resources to start analysis.
Finally, in order to avoid the situation that the video segments which are short in time and cannot be continuously fragmented exist in the storage, and the vacant resources are immediately analyzed and completed, a strategy of re-fragmenting the video segments is provided. The strategy is as follows:
after one fragment analysis finishes vacating analysis resources, according to the formula (3)
ts′＝ts+(ts-te) X p formula (3)
And calculating new initial analysis time of other fragments.
Wherein, ts' New starting analysis time for other slices, tsFor the start of the recorded segment to be processed, teAnd p is the analysis progress of the video clip.
And then, according to the new initial analysis time, carrying out fragmentation again according to the fragmentation formula, and then allocating resources to start analysis.
The following is a description of a specific embodiment:
example one
Establishing a video analysis task for 1 IPC, wherein the case-sending time is 16:00-17 in 2019, 7 and 04 pm: 30. the total number of analysis resources of the system is 100, the used analysis resources are 90, the available analysis resources are 10, and the minimum fragmentation time is 5 minutes.
The set-up parsing task time is 16:00-17:30 in 04 pm, 7 months in 2019. The video recording is not continuous in actual storage, and two segments of video recording are 16:00:00-16:20:02 and 16:30:00-17:30:00 in 04 afternoon in 7 months in 2019 respectively.
The optimal number of slices is 10 according to available analysis resources. The maximum sharable number of the 16:00:00-16:20:02 video recording segments is 4, the maximum sharable number of the 16:30:00-17:30:00 video recording segments is 12, and the maximum sharable number of the video recording segments is 16. According to the maximum sharable number ratio, the video segment of 16:00:00-16:20:02 needs to be divided into 3 pieces, and the video segment of 16:30:00-17:30:00 needs to be divided into 7 pieces (the calculation process is that EA is 10, N is 2, T1 is 20, T2 is 60, and tmin is 5.1 + (10-2) x 60/5 x 1/16 is 7). The post-creation-task sharding logic is shown in FIG. 2.
After the video logic fragmentation is completed, resources are allocated and analyzed, and task management/exception detection is started
The maximum abnormal times obtained by 10 pieces of the pieces is 30 times, and in actual work, if the trial times are set too few, the situation that the task is changed into abnormal due to an accidental error can easily occur; preferably, in this embodiment, the maximum abnormal number may be set to be 3 times of the fragmentation number according to an empirical value, where the maximum abnormal number is 10 × 3 — 30, which is equally shared by each subtask to be 3 opportunities, and when the abnormal number of the logical fragmentation task is accumulated to be greater than 30, the allocated resources are released, and the status of the video recording task is updated from the running status to the abnormal status. After waiting for 1 minute, resources are reallocated to attempt analysis.
Accordingly, the present embodiment also provides a computer-readable storage medium on which a computer program is stored, which when executed by a processor implements any one of the methods in the present embodiment.
The present embodiment further provides an electronic terminal, including: a processor and a memory;
the memory is used for storing computer programs, and the processor is used for executing the computer programs stored by the memory so as to enable the terminal to execute the method in the embodiment.
The computer-readable storage medium in the present embodiment can be understood by those skilled in the art as follows: all or part of the steps for implementing the above method embodiments may be performed by hardware associated with a computer program. The aforementioned computer program may be stored in a computer readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
The electronic terminal provided by the embodiment comprises a processor, a memory, a transceiver and a communication interface, wherein the memory and the communication interface are connected with the processor and the transceiver and are used for completing mutual communication, the memory is used for storing a computer program, the communication interface is used for carrying out communication, and the processor and the transceiver are used for operating the computer program so that the electronic terminal can execute the steps of the method.
In this embodiment, the Memory may include a Random Access Memory (RAM), and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory.
The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the Integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
In the above-described embodiments, reference in the specification to "the embodiment," "an embodiment," "another embodiment," or "other embodiments" means that a particular feature, structure, or characteristic described in connection with the embodiments is included in at least some embodiments, but not necessarily all embodiments. The various appearances of the phrase "the present embodiment," "one embodiment," or "another embodiment" are not necessarily all referring to the same embodiment. If the specification states a component, feature, structure, or characteristic "may", "might", or "could" be included, that particular component, feature, structure, or characteristic is not necessarily included. If the specification or claim refers to "a" or "an" element, that does not mean there is only one of the element. If the specification or claim refers to "a further" element, that does not preclude there being more than one of the further element.
In the embodiments described above, although the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those skilled in the art in light of the foregoing description. For example, other memory structures (e.g., dynamic ram (dram)) may use the discussed embodiments. The embodiments of the invention are intended to embrace all such alternatives, modifications and variances that fall within the broad scope of the appended claims.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The invention is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
The invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (8)
1. A discontinuous fragmentation acceleration method for storage video is characterized in that,
the method comprises the following steps of collecting video segments to be processed, and carrying out fragmentation processing on the video segments to be processed, wherein the fragmentation processing comprises the following steps:
acquiring the maximum fragment number of a video segment to be processed according to the minimum fragment time and the time of each video segment;
calculating the proportion of the maximum fragment number of each video segment to the maximum fragment number of the video segment to be processed;
acquiring the number of newly added segments of each corresponding video segment according to the proportion;
and performing resource allocation and video analysis according to the fragmentation processing result and the remaining available analysis resources, when the fragmentation analysis is completed and the analysis resources are vacated, performing the fragmentation processing on the video segments subjected to the fragmentation processing again, and performing video analysis on the video segments subjected to the fragmentation processing again and the reallocation resources.
2. The method according to claim 1, wherein when a fragment analysis completes and frees up analysis resources, a new start analysis time of another fragment is obtained, and the fragment processing is performed again according to the new start analysis time of the other fragment.
3. The method for accelerating fragments aiming at discontinuous storage video according to claim 2, wherein new start analysis time of other fragments is obtained according to the original start time and the original end time of the other fragments and the analysis progress of the fragments;
the starting analysis time of the other fragments is obtained by the following formula:
ts′＝ts+(ts-te)×p
wherein, ts' New starting analysis time for other slices, tsFor the start of the recorded segment to be processed, teAnd p is the analysis progress of the video clip.
4. The method for accelerating discontinuous fragmentation of stored video according to claim 1, wherein the number of fragments to be newly added to each current video segment is respectively obtained according to the remaining analysis resource amount at the current time and the actual number of video fragments stored at the current time, so as to obtain the final number of fragments of the whole video segment;
acquiring the number of the newly added fragments required for each corresponding video segment by the following formula:
where EA is the remaining analysis resources at a certain time, N is the number of actual video segments stored in a time period, and T isnFor the duration of the video segment of the nth segment, tminM is the number of fragments finally obtained, and is the minimum time length for which fragmentation can be performed.
5. The method for accelerating fragmentation aiming at discontinuous storage of video recordings according to any one of claims 1 to 4, characterized in that a maximum abnormal time threshold is obtained according to the fragmentation processing result, and when the cumulative number of abnormal times of the logical fragmentation task exceeds the maximum abnormal time threshold, the allocated resources are released and the video recording task state is updated from a running state to an abnormal state.
6. The method of claim 5, wherein a waiting time threshold is preset, and when the waiting time threshold is reached after the allocated resources are released and the video recording task status is updated from the running status to the abnormal status, the resources are reallocated for the trial analysis.
7. A computer-readable storage medium having stored thereon a computer program, characterized in that: the program when executed by a processor implements the method of any one of claims 1 to 6.
8. An electronic terminal, comprising: a processor and a memory;
the memory is for storing a computer program and the processor is for executing the computer program stored by the memory to cause the terminal to perform the method of any of claims 1 to 6.
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| CN109684088A (en) * | 2018-12-17 | 2019-04-26 | 南京理工大学 | The remote sensing big data of cloud platform resource constraint quickly handles method for scheduling task |
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| CN102801623A (en) * | 2012-08-15 | 2012-11-28 | 杭州华三通信技术有限公司 | Multi-access data transmitting method and device |
| CN107548490A (en) * | 2014-12-26 | 2018-01-05 | 英特尔公司 | Humidometer in parallel computation |
| CN109684088A (en) * | 2018-12-17 | 2019-04-26 | 南京理工大学 | The remote sensing big data of cloud platform resource constraint quickly handles method for scheduling task |
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