CN113115051B - High-definition video transmission and storage device - Google Patents
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Abstract
The invention discloses a data transmission and storage device for lossless compression coding and decoding of high-definition videos, which comprises a video acquisition unit, a video analysis unit, a video classification unit, a management unit, a processor, a conventional storage unit, a display unit, a data forwarding unit, a first storage unit, a second storage unit and a self-management unit, wherein the video acquisition unit is used for acquiring video data; the video acquisition unit is used for acquiring a real-time video around the automobile and transmitting the real-time video to the video analysis unit, and the video analysis unit receives the real-time video transmitted by the video acquisition unit and performs distance comparison analysis on the real-time video to obtain a segmented video and an inner distance value and an inner ring value corresponding to the segmented video; the video acquisition unit is used for acquiring real-time videos around the automobile, and the video analysis unit is used for carrying out distance comparison analysis on the real-time videos to obtain segmented videos and corresponding inner distance values and inner ring values of the segmented videos; and then, the video grading unit is used for grading and analyzing the segmented video, the corresponding inner distance value and the corresponding inner ring value to obtain a tail mark corresponding to the segmented video.
Description
Technical Field
The invention belongs to the field of video screen storage and transmission, and particularly relates to a high-definition video transmission and storage device.
Background
Patent publication No. CN107066581A discloses a distributed traffic monitoring video data storage and fast retrieval system, which includes: the video data storage module is connected with the HBase distributed column-type database and used for storing the video data into the HBase distributed column-type database; the distributed video data semantic retrieval module is used for establishing a memory-based structural index model for video data semantics; and the data communication module is used for data communication among a plurality of video data producers, a plurality of video data storage modules and the distributed video data semantic retrieval module. The data retrieval can be rapidly carried out according to the video semantic information, the retrieved video data can be rapidly obtained in batches, and the retrieval efficiency is remarkably improved while the storage of the video data is realized.
However, in the field of automobiles, particularly when storing a video related to an automobile record, it is not possible to identify the degree of importance with respect to the characteristics of the video, and a solution is provided based on the fact that different storage methods are selected according to the degree of importance.
Disclosure of Invention
The invention aims to provide a high-definition video transmission and storage device.
The purpose of the invention can be realized by the following technical scheme:
the high-definition video transmission storage device comprises a video acquisition unit, a video analysis unit, a video classification unit, a management unit, a processor, a conventional storage unit, a display unit, a data forwarding unit, a first storage unit, a second storage unit and a self-management unit;
the video acquisition unit is used for acquiring a real-time video around the automobile and transmitting the real-time video to the video analysis unit, and the video analysis unit receives the real-time video transmitted by the video acquisition unit and performs distance comparison analysis on the real-time video to obtain a segmented video and an inner distance value and an inner ring value corresponding to the segmented video;
the video analysis unit is used for transmitting the corresponding segmented video, the inner distance value and the inner ring value thereof to the video grading unit, and the video grading unit receives the segmented video transmitted by the video analysis unit, the inner distance value and the inner ring value thereof and carries out grading analysis on the segmented video to obtain a tail mark corresponding to the segmented video;
the video grading unit is used for transmitting the segmented video and the corresponding tail mark thereof to the processor, and the processor receives the segmented video transmitted by the video grading unit and the corresponding tail mark thereof; the processor is used for transmitting the tail mark and the segmented video thereof to a conventional storage unit for real-time storage;
the processor is used for performing unloading analysis on the tail mark and the segmented video thereof stored in the conventional storage unit, and the concrete unloading analysis steps are as follows:
and (4) SS1: acquiring all segmented videos, tail marks and storage time stored in a conventional storage unit;
and (4) SS2: marking all segmented videos as Fj, j =1.. M; correspondingly marking the memory occupation value of the segmented video as a memory occupation value Cj, wherein j =1.. M;
and (4) SS3: according to the storage time of all the segmented videos Fj, the time when the corresponding segmented videos are at the beginning of storage and the distance is the current is automatically obtained, the time is marked as a time distance value, the time is correspondingly marked as Pj, j =1.. M, and the Pj and the Fj are in one-to-one correspondence;
and (4) SS: then, defining a weighting ratio according to the tail mark of the corresponding stored video, specifically:
when the mark is the first grade mark, the weight gain ratio is assigned to 0.65;
when secondary, the weight gain ratio was assigned to 0.85;
when the mark is the final stage, the weight gain ratio is assigned to 1.15;
obtaining the weight gain ratio of all segmented videos, and marking the weight gain ratio as Qj, wherein j =1.. M;
and SS5: obtaining a storage value Cj, a time distance value Pj and a weight gain ratio Qj; and (3) calculating the adjustment value Uj according to a formula, wherein the specific calculation formula is as follows:
Uj=（0.483*Cj+0.517*Pj）*Qj；
and SS6: processing the Uj once every T2 time interval, specifically, sequencing the Uj in a descending order, and marking thirty percent of Uj before ranking as a re-segmentation video; marking thirty percent of the ranked videos as idle segmented videos, and marking the rest videos as conventional videos;
the processor is used for transmitting the re-segmented video, the idle segmented video and the conventional video to the data forwarding unit, the data forwarding unit is used for forwarding the re-segmented video to the first storage unit, and the first storage unit is cloud storage equipment and used for performing backup storage on the re-segmented video;
and the data forwarding unit is used for transmitting the idle segmented video to the second storage unit, and the second storage unit receives the idle segmented video transmitted by the data forwarding unit and stores the idle segmented video in real time.
Further, the video acquisition unit is a video acquisition device, specifically a camera, disposed on the automobile.
Further, the specific steps of the distance analysis are as follows:
the method comprises the following steps: acquiring a real-time video; intercepting the real-time video once at a specified time T1 at intervals to obtain a segmented video;
step two: when a new segmented video is obtained, automatically performing video analysis in the third step;
step three: obtaining all moving objects in the corresponding segmented video, and marking the moving objects as Wi, i =1.. N;
step four: acquiring the subtend values Di of all moving objects from the automobile, wherein i =1.. N;
step five: acquiring all the opposite values Di, rearranging the opposite values according to the sequence from small to large, associating corresponding moving objects Wi, and arranging D1 to be the minimum value in the automobile opposite values;
step six: comparing Di with X1, obtaining the number of opposite values of which Di is smaller than X1, and marking the number as an inner distance value; the total number n at this time is marked as the value in the loop.
Further, the specific manner of obtaining the counter value in step four is as follows:
s1: acquiring the longest distance of the automobile front cover in the corresponding video, and marking the longest distance as Cz;
s2: then, the lattice number of the pixel lattices occupied by the longest distance line corresponding to the front cover of the automobile is obtained and marked as the corresponding lattice number, and the CZ is divided by the corresponding lattice number to obtain a conversion value Zh;
s3: let i =1, select the corresponding moving object W1;
s4: acquiring a shortest path of a corresponding moving object from the edge of the automobile, acquiring a pixel grid of the shortest path, marking the corresponding pixel grid as a short-distance grid, and multiplying the short-distance grid by Zh to obtain a subtend value;
s5: let i = i +1;
s6: and repeating the steps S4-S6 until the opposite values Di of all the moving objects Wi are obtained.
Further, the specific steps of the hierarchical analysis are as follows:
s01: acquiring a corresponding segmented video, and an inner distance value and an inner ring value corresponding to the segmented video;
s02: and calculating a combined risk value according to the inner distance value and the inner ring value, wherein the combined risk value is calculated in a specific mode as follows:
combined risk value = 0.654/inner distance value +0.346 inner loop value;
s03: after the combination risk value is obtained, the combination risk value is judged, specifically as follows:
when the combination risk value is more than or equal to X2, the corresponding segmented video is endowed with a tail mark at the moment, and the tail mark at the moment is a first-level mark;
when X3< combination risk value < X2, the tail at this time is marked as a secondary mark;
when the combination risk value is < X3, the tail at this time is marked as the last level;
s04: and obtaining the segmented video and the corresponding tail mark thereof.
Further, the self-management unit is configured to perform management analysis on the lazy segment video stored in the second storage unit, where the specific management analysis steps are as follows:
SS01: obtaining a lazy segmented video in a second storage unit;
SS02: acquiring the calling times of all the lazy segmented videos and the time when the distance between the calling time and the corresponding calling time is the last time, and marking the time as the back distance time;
SS03: when the storage capacity of the second storage unit exceeds X4, automatically entering the step SS04 for storage deletion, wherein X4 is a preset value;
SS04: acquiring all back distance time, calling times and occupation values; calculating deletion values of all the inert segmented videos, wherein the specific calculation formula is as follows:
the deleted value =0.321 × post-interval time + 0.288/call count +0.391 deposit value;
SS05: and sequencing the lazy segmented videos according to the sequence of the deleting values from large to small, deleting the deleting values from large to small in sequence until the vacant storage space of the corresponding second storage unit exceeds X5, stopping deleting, wherein X5 is larger than X4, and X5 is a preset value.
The invention has the beneficial effects that:
the video acquisition unit is used for acquiring real-time videos around the automobile, and the video analysis unit is used for carrying out distance comparison analysis on the real-time videos to obtain segmented videos and corresponding inner distance values and inner ring values of the segmented videos; then, carrying out grading analysis on the segmented video and the corresponding inner distance value and the corresponding inner ring value thereof by means of a video grading unit to obtain a tail mark corresponding to the segmented video;
the processor transmits the tail mark and the segmented video thereof to a conventional storage unit for real-time storage; simultaneously, the tail mark and the segmented video thereof stored in the conventional storage unit are subjected to dump analysis to obtain a re-segmented video, a passive segmented video and a conventional video; then, transmitting the re-segmented video, the idle segmented video and the conventional video to different storage units for backup or storage according to related requirements; the invention is simple, effective and easy to use.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is a block diagram of the system of the present invention.
Detailed Description
As shown in fig. 1, the storage device for high definition video transmission includes a video acquisition unit, a video parsing unit, a video classification unit, a management unit, a processor, a conventional storage unit, a display unit, a data forwarding unit, a first storage unit, a second storage unit, and a self-management unit;
the system comprises a video acquisition unit, a video processing unit and a video processing unit, wherein the video acquisition unit is video acquisition equipment arranged on an automobile, and specifically is a camera or a vehicle event data recorder and the like; the video acquisition unit is used for acquiring real-time videos around the automobile and transmitting the real-time videos to the video analysis unit, the video analysis unit receives the real-time videos transmitted by the video acquisition unit and carries out distance alignment analysis on the real-time videos, and the distance alignment analysis comprises the following specific steps:
the method comprises the following steps: acquiring a real-time video; intercepting the real-time video once at a specified time T1 at intervals to obtain a segmented video;
step two: when a new segmented video is obtained, automatically performing video analysis in the third step;
step three: obtaining all moving objects in the corresponding segmented video, and marking the moving objects as Wi, i =1.. N;
step four: obtaining the subtend values of all moving objects from the automobile, wherein the specific subtend value obtaining mode is as follows:
s1: acquiring the longest distance of the automobile front cover in the corresponding video, and marking the longest distance as Cz;
s2: then, the lattice number of the pixel lattices occupied by the longest distance line corresponding to the front cover of the automobile is obtained and marked as the corresponding lattice number, and the CZ is divided by the corresponding lattice number to obtain a conversion value Zh;
s3: let i =1, select the corresponding moving object W1;
s4: obtaining the shortest path of a corresponding moving object from the edge of the automobile, obtaining a pixel grid of the shortest path, marking the corresponding pixel grid as a short-distance grid, and multiplying the short-distance grid by Zh to obtain a subtend value Di;
s5: let i = i +1;
s6: repeating the steps S4 to S6 until the subtending values Di of all the moving objects Wi are obtained;
step five: acquiring all the subtend values Di, rearranging the subtend values according to the sequence from small to large, associating the corresponding moving objects Wi, and taking D1 as the minimum value in the automobile subtend values after rearrangement;
step six: comparing Di with X1, obtaining the number of opposite values of which Di is smaller than X1, and marking the number as an inner distance value; marking the total number n at the moment as an intra-loop value, wherein X1 is a preset value;
the video analysis unit is used for transmitting the corresponding segmented video, the inner distance value and the inner ring value thereof to the video grading unit, the video grading unit receives the segmented video transmitted by the video analysis unit, the inner distance value and the inner ring value thereof and carries out grading analysis on the segmented video, and the grading analysis specifically comprises the following steps:
s01: acquiring a corresponding segmented video, and an inner distance value and an inner ring value corresponding to the segmented video;
s02: and calculating a combined risk value according to the inner distance value and the inner ring value, wherein the combined risk value is calculated in a specific mode as follows:
combined risk value = 0.654/inner distance value +0.346 inner loop value;
s03: after obtaining the combination risk value, judging the combination risk value, specifically:
when the combination risk value is larger than or equal to X2, the corresponding segmented video is endowed with a tail mark at the moment, and the tail mark at the moment is a first-level mark;
when X3< combination risk value < X2, the tail at this time is marked as a secondary mark;
when the combined risk value < X3, the tail at this time is marked as the last level mark;
s04: obtaining a segmented video and a corresponding tail mark thereof, wherein X2 and X3 are preset values;
the video grading unit is used for transmitting the segmented video and the corresponding tail mark thereof to the processor, and the processor receives the segmented video transmitted by the video grading unit and the corresponding tail mark thereof; the processor is used for transmitting the tail mark and the segmented video thereof to a conventional storage unit for real-time storage;
the processor is used for performing unloading analysis on the tail mark and the segmented video thereof stored in the conventional storage unit, and the concrete unloading analysis steps are as follows:
and (4) SS1: acquiring all segmented videos, tail marks and storage time stored in a conventional storage unit;
and SS2: marking all segmented videos as Fj, j =1.. M; correspondingly marking the memory occupation value of the segmented video as a memory occupation value Cj, j =1.. M;
and (4) SS3: according to the storage time of all the segmented videos Fj, the time when the corresponding segmented videos are at the beginning of storage and the distance is the current is automatically obtained, the time is marked as a time distance value, the time is correspondingly marked as Pj, j =1.. M, and the Pj and the Fj are in one-to-one correspondence;
and SS4: then, defining a weighting ratio according to the tail mark of the corresponding stored video, specifically:
when the mark is the first grade mark, the weight gain ratio is assigned to 0.65;
when secondary label, the weight gain ratio was assigned 0.85;
when the final mark is used, the weight gain ratio is assigned to 1.15;
obtaining the weight gain ratio of all segmented videos, and marking the weight gain ratio as Qj, wherein j =1.. M;
SS5: obtaining a storage value Cj, a time distance value Pj and a weight gain ratio Qj; and calculating the adjustment value Uj according to a formula, wherein the specific calculation formula is as follows:
Uj=（0.483*Cj+0.517*Pj）*Qj；
and SS6: processing the Uj once every T2 time interval, specifically, sequencing the Uj in a descending order, and marking thirty percent of Uj before ranking as a re-segmentation video; marking thirty percent of the videos after ranking as inert segmented videos, and marking the rest videos as conventional videos;
the processor is used for transmitting the re-segmented video, the lazy segmented video and the conventional video to the data forwarding unit, the data forwarding unit is used for transferring the re-segmented video to the first storage unit, and the first storage unit is cloud storage equipment and used for backing up and storing the re-segmented video;
the data forwarding unit is used for transmitting the idle segmented video to the second storage unit, and the second storage unit receives the idle segmented video transmitted by the data forwarding unit and stores the idle segmented video in real time;
the self-management unit is used for managing and analyzing the lazy segment video stored in the second storage unit, and the specific management and analysis steps are as follows:
SS01: obtaining a lazy segmented video in a second storage unit;
and SS02: acquiring the calling times of all the lazy segmented videos and the time corresponding to the distance between the last calling time and the current calling time, and marking the time as the back distance time;
SS03: when the storage capacity of the second storage unit exceeds X4, automatically entering the step SS04 for storage deletion, wherein X4 is a preset value;
and (4) SS04: acquiring all back distance time, calling times and occupation values; calculating deletion values of all the lazy segmented videos, wherein the specific calculation formula is as follows:
the deleted value =0.321 × post-interval time + 0.288/call count +0.391 deposit value;
SS05: and sequencing the lazy segmented videos according to the sequence of the deletion values from large to small, deleting the deletion values from large to small in sequence, and stopping deleting until the vacant storage space of the corresponding second storage unit exceeds X5, wherein X5 is larger than X4, and X5 is a preset value.
The high-definition video transmission storage device is used for acquiring real-time videos around the automobile through the video acquisition unit when working, and performing distance comparison analysis on the real-time videos by means of the video analysis unit to obtain segmented videos and corresponding inner distance values and inner ring values of the segmented videos; then, the video grading unit is used for grading and analyzing the segmented video and the corresponding inner distance value and the corresponding inner ring value of the segmented video to obtain a tail mark corresponding to the segmented video;
the processor transmits the tail mark and the segmented video thereof to a conventional storage unit for real-time storage; simultaneously, the tail mark and the segmented video thereof stored in the conventional storage unit are subjected to dump analysis to obtain a re-segmented video, a passive segmented video and a conventional video; then, the re-segmented video, the inert segmented video and the conventional video are transmitted to different storage units for backup or storage according to related requirements; the invention is simple, effective and easy to use.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (4)
1. A high-definition video transmission storage device is characterized by comprising a video acquisition unit, a video analysis unit, a video classification unit, a management unit, a processor, a conventional storage unit, a display unit, a data forwarding unit, a first storage unit, a second storage unit and a self-management unit;
the video acquisition unit is used for acquiring a real-time video around the automobile and transmitting the real-time video to the video analysis unit, and the video analysis unit receives the real-time video transmitted by the video acquisition unit and performs distance comparison analysis on the real-time video to obtain a segmented video and an inner distance value and an inner ring value corresponding to the segmented video;
the video analysis unit is used for transmitting the corresponding segmented video, the inner distance value and the inner ring value thereof to the video grading unit, and the video grading unit receives the segmented video transmitted by the video analysis unit, the inner distance value and the inner ring value thereof and carries out grading analysis on the segmented video to obtain a tail mark corresponding to the segmented video;
the video grading unit is used for transmitting the segmented video and the corresponding tail mark thereof to the processor, and the processor receives the segmented video transmitted by the video grading unit and the corresponding tail mark thereof; the processor is used for transmitting the tail mark and the segmented video thereof to a conventional storage unit for real-time storage;
the processor is used for performing unloading analysis on the tail mark and the segmented video thereof stored in the conventional storage unit, and the concrete unloading analysis steps are as follows:
and (4) SS1: acquiring all segmented videos, tail marks and storage time stored in a conventional storage unit;
and (4) SS2: marking all segmented videos as Fj, j =1.. M; correspondingly marking the memory occupation value of the segmented video as a memory occupation value Cj, j =1.. M;
and SS3: according to the storage time of all segmented videos Fj, automatically acquiring the time when the distance of the corresponding segmented video starts to be the current distance value when the storage starts, marking the time as a time distance value, marking the time as Pj correspondingly, wherein j =1.. M, and the Pj and the Fj are in one-to-one correspondence;
and (4) SS: then, defining a weighting ratio according to the tail mark of the corresponding stored video, specifically:
when the mark is the first grade mark, the weight gain ratio is assigned to 0.65;
when secondary label, the weight gain ratio was assigned 0.85;
when the mark is the final stage, the weight gain ratio is assigned to 1.15;
obtaining the weight gain ratio of all segmented videos, and marking the weight gain ratio as Qj, j =1.. M;
and SS5: obtaining a storage value Cj, a time distance value Pj and a weight gain ratio Qj; and (3) calculating the adjustment value Uj according to a formula, wherein the specific calculation formula is as follows:
Uj=（0.483*Cj+0.517*Pj）*Qj；
and SS6: processing the Uj once every T2 time interval, specifically, sequencing the Uj in a descending order, and marking thirty percent of Uj before ranking as a re-segmentation video; marking thirty percent of the ranked videos as idle segmented videos, and marking the rest videos as conventional videos;
the processor is used for transmitting the re-segmented video, the idle segmented video and the conventional video to the data forwarding unit, the data forwarding unit is used for forwarding the re-segmented video to the first storage unit, and the first storage unit is cloud storage equipment and used for performing backup storage on the re-segmented video; the data forwarding unit is used for transmitting the inert segmented video to the second storage unit, and the second storage unit receives the inert segmented video transmitted by the data forwarding unit and stores the inert segmented video in real time;
the specific steps of the distance analysis are as follows:
the method comprises the following steps: acquiring a real-time video; intercepting the real-time video once at a specified time T1 at intervals to obtain a segmented video;
step two: when a new segmented video is obtained, automatically performing video analysis in the third step;
step three: obtaining all moving objects in the corresponding segmented video, and marking the moving objects as Wi, i =1.. N;
step four: acquiring the subtend values Di of all moving objects from the automobile, wherein i =1.. N;
step five: rearranging the subtend values according to the sequence from small to large, associating the subtend values with corresponding moving objects Wi, and taking D1 as the minimum value in the automobile subtend values after rearrangement;
step six: comparing Di with X1, acquiring the number of opposite values of which Di is smaller than X1, and marking the number as an inner distance value; marking the total number n at the moment as an intra-ring value, wherein X1 is a preset value;
the specific way of obtaining the subtended value in the fourth step is as follows:
s1: acquiring the longest distance of the automobile front cover in the corresponding video, and marking the longest distance as Cz;
s2: then, acquiring the number of grids of the pixel grids occupied by the longest distance line corresponding to the front cover of the automobile, marking the grids as corresponding grids, and dividing Cz by the corresponding grids to obtain a conversion value Zh;
s3: let i =1, select the corresponding moving object W1;
s4: obtaining the shortest path of a corresponding moving object from the edge of the automobile, obtaining a pixel grid of the shortest path, marking the corresponding pixel grid as a short-distance grid, and multiplying the short-distance grid by Zh to obtain a subtend value Di;
s5: let i = i +1;
s6: and repeating the steps S4 to S5 until the subtended values Di of all the moving objects Wi are obtained.
2. The apparatus according to claim 1, wherein the video capture unit is a video capture device, specifically a video camera, installed in an automobile.
3. The device for transmitting and storing high definition video according to claim 1, wherein the specific steps of the hierarchical analysis are as follows:
s01: acquiring a corresponding segmented video, and an inner distance value and an inner ring value corresponding to the segmented video;
s02: and calculating a combined risk value according to the inner distance value and the inner ring value, wherein the combined risk value is calculated in a specific mode as follows:
combined risk value = 0.654/inner distance value +0.346 inner loop value;
s03: after obtaining the combination risk value, judging the combination risk value, specifically:
when the combination risk value is larger than or equal to X2, the corresponding segmented video is endowed with a tail mark at the moment, and the tail mark at the moment is a first-level mark;
when X3< combination risk value < X2, the tail at this time is marked as a secondary mark;
when the combination risk value is < X3, the tail at this time is marked as the last level;
s04: and obtaining the segmented video and the corresponding tail mark thereof, wherein X2 and X3 are preset values.
4. The device for transmitting and storing high-definition videos according to claim 1, wherein the self-management unit is configured to perform management analysis on the lazy segment videos stored in the second storage unit, and the specific management analysis steps include:
SS01: obtaining a lazy segmented video in a second storage unit;
and SS02: acquiring the calling times of all the lazy segmented videos and the time corresponding to the distance between the last calling time and the current calling time, and marking the time as the back distance time;
SS03: when the storage capacity of the second storage unit exceeds X4, the step SS04 is automatically entered for storage deletion, and X4 is a preset value;
SS04: acquiring all back distance time, calling times and occupation values; calculating deletion values of all the inert segmented videos, wherein the specific calculation formula is as follows:
delete value =0.321 × lag time + 0.288/number of calls +0.391 count value;
SS05: and sequencing the lazy segmented videos according to the sequence of the deletion values from large to small, deleting the deletion values from large to small in sequence, and stopping deleting until the vacant storage space of the corresponding second storage unit exceeds X5, wherein X5 is larger than X4, and X5 is a preset value.
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| KR20130066828A (en) * | 2011-12-13 | 2013-06-21 | 주식회사 위츠 | Real time video transferring system for vehicle installation |
| CN111601080A (en) * | 2020-05-12 | 2020-08-28 | 杭州武盛广告制作有限公司 | Video management system for community security monitoring video storage |
| CN112601052A (en) * | 2020-12-10 | 2021-04-02 | 四川警察学院 | Video resource integration system applied to internal sharing platform |
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