CN115640422A - Network media video data analysis and supervision system - Google Patents
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Abstract
The invention discloses a network media video data analysis and supervision system which comprises a local system, a cloud platform system and a cloud computing system, wherein the local system is provided with video processing software and office software and is used for editing a source video to be analyzed and supervised and remarking key description; the cloud platform system comprises a data uploading module, a data downloading module and an analysis data cloud access module; the cloud computing system comprises a cloud operation rule program and a data cloud access module. The method is simple to use, can quickly and accurately acquire the playing condition and the fission dynamics of the source video at low cost, obtains the suggestion of high-efficiency supervision and limitation or promotion of transmission, and has remarkable technical progress significance for preventing the transmission of harmful videos, refusing the infringement of original intellectual property rights of the videos, accurately putting advertisements and promoting the transmission and fission of beneficial videos.
Description
Technical Field
The invention relates to the field of video big data supervision, in particular to a network media video data analysis and supervision system.
Background
CN110740290B discloses a method and an apparatus for previewing a surveillance video, which solve the problem that in the field of video surveillance, when a user queries a surveillance video of an interest event in the surveillance video, the query process takes time when the specific time of the occurrence of the interest event is unknown, in this scheme, a request for previewing the surveillance video includes the surveillance video to be previewed and a time sequence of each key frame in the surveillance video. And then, the video storage equipment searches the corresponding monitoring video and a plurality of key frames of the monitoring video according to the monitoring video preview request and sends the key frames to the user terminal. And then, the user terminal plays the monitoring video and decodes the plurality of key frames in the playing process to obtain a plurality of corresponding preview pictures. And finally, presenting the plurality of preview pictures on the current playing node of the monitoring video in a preview axis form. Therefore, the preview information is more by presenting the plurality of preview pictures in the form of the preview axis, the user is helped to quickly preview the monitoring video and find the interesting event more quickly, and in addition, the application consumes less calculation performance and can be suitable for different terminal platforms.
CN103455550B discloses a method and an apparatus for obtaining an image search result with a contrast effect, which solve the problem that when a user has multiple search requirements, a keyword is input, and an image containing the keyword in a text around the image is searched as a search result and returned to the user, if the image search engine reflected by the keyword cannot judge this, or the returned result only reflects one of the search requirements, and the search requirement does not meet the intention of the user, the user can obtain a satisfactory image only by searching for multiple times, so that effective extraction and contrast of the keyword and the image are realized, and the user can obtain multiple images for comparison that the user wants to retrieve as soon as possible.
CN103530656B discloses an image summary generation method based on hidden structure learning, which has higher information coverage rate and lower redundancy, can implicitly learn different preferences of different theme-related image sets in feature selection, and achieves better effects than the conventional method. CN103617261B discloses a method and a system for identifying content attributes of pictures, which can perform similar picture identification on collected pictures and aggregate the pictures into a plurality of homologous picture clusters; calculating the relative transfer number of a plurality of homologous image clusters to a specific resource station; and identifying the corresponding picture content attribute in the homologous picture cluster according to the relative transfer number, which is particularly effective for judging whether the picture is an advertisement picture.
CN111414842B discloses a video comparison method, apparatus, computer device and storage medium, which can obtain a first video (i.e. the source video of the present invention) and a second video (i.e. the video to be compared for which the preliminary matching of the present invention is successful); then acquiring a first image sequence from the first video and acquiring a second image sequence from the second video; then, extracting a first definition feature vector of the first image sequence through a first feature extraction module of the video comparison model; the second feature extraction module through the video contrast model extracts the second definition feature vector of the second image sequence, the definition feature vectors of the two image sequences can reflect the relative condition of the definition of the two videos more accurately, after the feature vectors are extracted, the definition difference analysis module of the video contrast model can be used for determining the definition difference of the first video and the second video based on the first definition feature vector and the second definition feature vector, the quantification of the definition difference of the two videos is realized, and the analysis accuracy of the definition difference of the videos is favorably improved.
In summary, the application level of the prior art is low, the prior art cannot be used for the transmission monitoring and control of specific video contents, the functions of quick early warning and control and management do not have timely risks to the video which is transmitted on the network and is harmful to the public order, and the behavior of stealing the original video intellectual property rights by illegal infringement on the network cannot be prevented.
Disclosure of Invention
The invention aims to overcome the problems in the prior art and provides a network media video data analysis and supervision system, which adopts a technical means of combining a local terminal installation commercial special software, a cloud platform and cloud computing, greatly reduces the hardware investment, the cost investment of computing power and the development cost of complex video processing software, can quickly and efficiently search various varieties of source videos in a network, can effectively monitor the propagation and diffusion range of the source videos and the varieties thereof, is favorable for users to accurately manage, monitor and control the network dynamics of the source videos, and reduces behaviors of lawbreakers using the network videos to carry out intellectual property infringement, illegal application, crimes and the like.
In order to achieve the technical purpose and achieve the technical effect, the invention is realized by the following technical scheme:
a network media video data analysis and supervision system comprises a local system, a cloud platform system and a cloud computing system, wherein the local system is provided with video processing software and office software and is used for editing a source video to be analyzed and supervised and remarking key description; the cloud platform system comprises a data uploading module, a data downloading module and an analysis data cloud access module; the cloud computing system comprises a cloud operation rule program and a data cloud access module;
the cloud platform system: the system also comprises a sample rapid preview generation module, a rapid preview key frame generation module, a key clipping calibration module and a network cloud video retrieval module;
the cloud operation rule program of the cloud computing system comprises a sample object importing program, a video retrieval result importing program, a video quick preview generating program, a video quick preview key frame generating program, a key frame comparison program, a quick preview comparison program, a comparison result data analysis program and an analysis result statistical output program;
the system also comprises the following operation steps:
1) Local processing of source video: including clipping, description and uploading; a video user acquires a source video, performs necessary editing by using video processing software installed in a local system, then describes the source video by using keywords, uploads the source video to a cloud platform system after the description is completed,
2) The cloud platform system starts the cloud computing system: the method comprises the steps of video retrieval, video import, quick preview generation, preview key frame comparison, quick preview comparison and comparative analysis data summarization generation; the cloud platform system generates video fast preview (namely source video preview) for a source video (namely source video), extracts key frames (namely source video key frames) of the source video fast preview, searches videos to be compared (namely network videos) meeting key word constraint conditions in a network according to key words, sequentially introduces the videos to be compared, sequentially generates video fast preview (namely network video preview) for the videos to be compared, further extracts key frames (namely network video key frames) of the videos to be compared for fast preview, firstly compares the difference between the key frames (namely source video key frames) of the source video fast preview and the key frames (namely network video key frames) of the videos to be compared, eliminates the videos to be compared with different key frame contrast details, the remaining videos to be compared enter a video fast comparison preview mode, compares the difference between the source video fast preview and the videos to be compared, eliminates the videos to be compared with inconsistent comparison results again, and outputs data analysis results of the videos to be compared;
3) Supervision analysis data application: the cloud computing system generates downloadable supervision analysis data, a user can check the data after checking the data on a cloud platform or downloading the data to a local system, and supervision measures are taken according to a data comparison result.
Preferably, the highlight clip calibration module is: a user circles an area on a key frame of the source video quick preview, the area selected by the circle is used as a supplement (namely the source video) of the key frame of the sample target, the area can be independently amplified, reduced, mirrored and turned, and then is compared with the key frame of the video quick preview to be compared, the video to be compared which does not accord with the comparison condition is directly eliminated, and the video to be compared which accords with the comparison condition starts a key frame comparison program.
Preferably, the network cloud video retrieval module is that the cloud platform system automatically acquires the description content of the source video from the user, extracts the keywords, and combines the keywords to perform video retrieval on the network.
Preferably, the video search result importing program: the cloud platform system retrieves videos related to the keywords according to the keyword combination, collects video websites and transmits the videos to the cloud computing system, the cloud computing system sequentially collects the related videos, generates corresponding fast previews of the videos to be compared and fast previews key frames to be compared for the related videos, and guides the fast previews key frames to be compared into a key frame comparison program of the cloud computing system.
Preferably, a key frame comparison procedure; the cloud computing system firstly introduces the supplement of the sample target key frame circled by the user or the key frame for fast previewing the source video, and if the supplement of the sample target key frame circled by the user exists, the key frame for fast previewing the source video is not introduced; secondly, importing the fast preview key frames to be compared, and comparing the two imported key frames; if the key frame of the sample target can be found in the fast preview key frames to be compared, the video fast preview corresponding to the fast preview key frames to be compared is led into the cloud computing system, and if the key frame of the sample target cannot be found in the fast preview key frames to be compared, the video fast preview and the related video corresponding to the fast preview key frames to be compared are excluded.
Preferably, in the rapid preview comparison program, the cloud computing system firstly imports rapid preview of a source video, secondly imports rapid preview of a video to be compared, and starts comparison on the two imported rapid preview of the video by taking a key frame as a joint point; if the continuous synchronous part with the fast preview (namely the source video preview) of the source video can be found in the fast preview (namely the network video preview) of the video to be compared, a synchronous time node is recorded, the synchronous duration is recorded, the key frame screenshots of the start and the end of the synchronization are recorded, the reference amplitude and the adaptation degree are calculated according to the accumulated synchronous times and the synchronous duration and the ratio of the source video to the comparison video, and if the continuous synchronous part cannot be found in the fast preview of the video to be compared, the related video of the corresponding fast preview of the video is excluded.
Preferably, the comparative result data analysis program: and analyzing the data result of the single video and the data result of the batch video, and performing secondary analysis on the related data of the single video to obtain the integral reference amplitude, the recomposition degree and the viewing diffusion fission index.
Preferably, in the monitoring measures, the user sets threshold values of reference amplitude and adaptation degree in the local system or the cloud platform system, sets monitoring treatment measures in each threshold value range interval for the reference amplitude and the adaptation degree, and obtains suggested feedback of the monitoring measures according to the monitoring treatment measures.
Preferably, the analysis result statistics output program compares and calculates the data by the cloud computing system to generate a graphic report, and the graphic report is stored in the cloud platform system for a user to check in the cloud platform system or to check after the graphic report is downloaded to a local system.
Preferably, the recommended feedback of the supervision action comprises: ignore, dynamically track, focus on, fission track, reference learning, limit or promote propagation.
The beneficial effects of the invention are:
(1) By adopting the technical means of combining the local terminal installation of the special commercial software, the cloud platform and the cloud computing, the hardware investment, the cost investment of computing power and the development cost and the human resource investment of complex video processing software are greatly reduced;
(2) The method is simple to operate, and as long as a user provides videos needing to be compared and makes keyword description on the videos, the playing situation and the fission dynamics of the source videos can be obtained quickly and accurately at low cost, efficient supervision limitation or suggestions for promoting propagation are obtained, and the method has remarkable technical progress significance for preventing propagation of harmful videos, refusing infringement of original intellectual property rights of the videos and accurately releasing advertisements and promoting propagation and fission of beneficial videos.
(3) The method can quickly and efficiently search various varieties of the source video in the network, can effectively monitor the spreading range of the source video and the varieties thereof, is beneficial to accurately managing, monitoring and controlling the network dynamics of the source video by a user, and reduces behaviors of infringement of intellectual property rights, illegal application, crimes and the like by lawbreakers by utilizing the network video.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical solutions of the present invention more clearly understood and to be implemented in accordance with the content of the specification, the following detailed description is made of preferred embodiments of the present invention in conjunction with the accompanying drawings. The detailed description of the present invention is given in detail by the following examples and the accompanying drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a schematic diagram of a technical module according to an embodiment of the present invention;
FIG. 2 is a flow chart illustrating operation of a network video system according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of video comparison logic and analysis flow according to an embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings:
referring to fig. 1 to 3, a user installs video picture processing software (e.g., AE, PR, DW, PS, etc.) and office software (e.g., office, WPS), etc. by using a local system (e.g., a computer device such as a desktop, a notebook, a server, etc.), and then edits, modifies, clips, fuses, etc. a source video (i.e., a source video) to be analyzed and supervised, and performs detailed modification description (i.e., keywords) on the source video by using colloquial and professional terms, so as to accurately describe the attribute properties of the video; after processing, importing the source video and the keywords into a cloud computing system by using a data uploading module of the cloud platform system, calculating to generate a source video fast preview and video retrieval keyword combination, further generating a source video fast preview key frame combination, combining the source video fast preview and source video fast preview key frames into a comparison reference object, at the moment, a user can check the source video fast preview key frame combination (namely, a source video preview key frame) and can use lines, graphs (boxes, circles, cursor track hand-drawn graphs) and the like to define key comparison contents (such as face close-up, cartoon modeling, clothes, vehicles, signs and the like), and after defining, the defined contents are additionally stored into a source video supplement key frame combination (namely, a source video supplement key frame) with priority for comparison, comparing the sequence priority of source video supplement key frames, source video preview key frames and source video fast preview, if the user does not add the source video supplement key frames, only comparing the source video fast preview key frame combination with the source video fast preview, namely 2-layer comparison, if the user adds the source video supplement key frames, firstly comparing the source video supplement key frames, secondly combining the source video fast preview key frames, and finally performing the source video fast preview, namely 3-layer comparison, although the user can also choose to cancel the comparison of the source video fast preview key frame combination, namely only comparing the source video supplement key frames with the source video fast preview, also 2-layer comparison, the cloud computing platform searches in the internet video search engine by using the video search key word combination at the background to obtain the video to be compared (namely the network video) conforming to the key word label, according to retrieval sequencing, generating fast previews for videos to be compared (namely network video fast previews), further generating key frame combinations (namely network video preview key frames) for the fast previews, starting a comparison mode after finishing the fast previews and the key frames of the current network videos, firstly taking source video supplement key frames defined by a user as comparison targets, searching for the same or similar blocks in the network video preview key frames by adopting algorithms such as translation, amplification, reduction, mirroring, turning, pixel resolution change and the like, and eliminating the network videos if the blocks meeting requirements cannot be found in all the key frame combinations, and then performing comparison of the next step; if more than one identical or similar block can be found, recording the video playing time corresponding to each matched block key frame as the synchronous starting time of the quick preview comparison; in default, after the comparison between the source video supplement key frame and the network video preview key frame is completed, the comparison between the source video preview key frame and the network video preview key frame is performed again for the network video preview key frame with the same or similar, the condition of the same or similar is confirmed and positioned again, the network video which is not in accordance with the condition is eliminated, the related data of the network video key frame with the same or similar is recorded more accurately, if the user does not circle the source video supplement key frame, the comparison between the source video supplement key frame and the network video preview key frame is ignored, the comparison between the source video preview key frame and the network video preview key frame is directly performed, after the comparison of the key frames is completed, the rapid comparison of the network video which is not eliminated is started, the rapid preview of the source video is taken as reference, the method comprises the steps of adopting algorithms of translation, amplification, reduction, mirroring, turning, pixel resolution change and the like for fast previewing a source video, searching a same or similar block with the source video in fast previewing the network video, eliminating misjudgments without continuous same or similar, excluding irrelevant network videos, recording the synchronous time of the start and the end of the same or similar network videos and the change difference of translation, amplification, reduction, mirroring, turning and pixel resolution change for the network videos which are not eliminated again, generating a relevant basic data report, extracting the synchronous time, the synchronous duration and the change difference of the network videos in the basic data report by a cloud computing system, analyzing and calculating the correlation degree and the synchronization degree among the videos, the occurrence time, the playing amount and the like of the network videos, further analyzing the track and the trend of network propagation and fission of the source video, and locking the key propagation nodes of video fission, giving out video propagation constraint or promoted supervision suggestions, and outputting the supervision suggestions to the cloud platform system for the user to directly view or download to a local system in the cloud platform system and then process.
The method is simple to use, and the terminal user only needs to provide the source video, describe the source video and upload the source video to the cloud platform, can manually circle key frame comparison key points, and can rapidly and accurately acquire the playing condition and fission dynamics of the source video at low cost without circle, and obtain suggestions for efficient supervision and limitation or promotion of propagation, so that the method has obvious technical progress significance for preventing propagation of harmful videos, refusing infringement of original intellectual property rights of videos and accurately releasing advertisements and promoting propagation and fission of beneficial videos.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A network media video data analysis and supervision system comprises a local system, a cloud platform system and a cloud computing system, wherein the local system is provided with video processing software and office software and is used for editing a source video to be analyzed and supervised and remarking key description; the cloud platform system comprises a data uploading module, a data downloading module and an analysis data cloud access module; the cloud computing system comprises a cloud operation rule program and a data cloud access module, and is characterized in that:
the cloud platform system: the system also comprises a sample rapid preview generation module, a rapid preview key frame generation module, a key clipping calibration module and a network cloud video retrieval module;
the cloud operation rule program of the cloud computing system comprises a sample target importing program, a video retrieval result importing program, a video quick preview generating program, a video quick preview key frame generating program, a key frame comparing program, a quick preview comparing program, a comparison result data analyzing program and an analysis result statistical output program;
the system also comprises the following operation steps:
1) Local processing of source video: including editing, describing, and uploading; a video user acquires a source video, performs necessary editing by using video processing software installed in a local system, then describes the source video by using keywords, uploads the source video to a cloud platform system after the description is completed,
2) The cloud platform system starts the cloud computing system: the method comprises the steps of video retrieval, video import, quick preview generation, preview key frame comparison, quick preview comparison and comparison analysis data summarization generation; the cloud platform system generates video fast preview for a source video, extracts a key frame of the source video fast preview, searches videos to be compared which accord with key word constraint conditions in a network according to key words, sequentially introduces the videos to be compared, sequentially generates video fast preview for the videos to be compared, further extracts the key frame of the video fast preview to be compared, compares the difference between the key frame of the source video fast preview and the key frame of the video fast preview to be compared, eliminates videos to be compared with different key frame contrast details, the remaining videos to be compared enter a video fast preview contrast mode, compares the difference between the source video fast preview and the video fast preview to be compared, eliminates videos to be compared which do not accord with the comparison result again, and outputs data analysis results of the videos to be compared which accord with the comparison result;
3) A regulatory analysis data application: the cloud computing system generates downloadable supervision analysis data, a user can check the data after checking the data on the cloud platform or downloading the data to the local system, and supervision measures are taken according to data comparison results.
2. The system of claim 1, wherein the system comprises: the key editing calibration module comprises: a user circles an area on a key frame of the source video quick preview, the area selected by the circle is used as a supplement of a sample target key frame, the area can be independently amplified, reduced, mirrored and turned, then the area is compared with the key frame of the video quick preview to be compared, the video to be compared which does not accord with the comparison condition is directly eliminated, and the video to be compared which accords with the comparison condition starts a key frame comparison program.
3. The system according to claim 1, wherein said system comprises: the network cloud video retrieval module is characterized in that a cloud platform system automatically acquires the description content of a user on a source video, extracts keywords and combines the keywords to perform video retrieval on a network.
4. The system of claim 1, wherein the system comprises: the video retrieval result importing program comprises: the cloud platform system retrieves videos related to the keywords according to the keyword combination, collects video websites and transmits the videos to the cloud computing system, the cloud computing system collects the related videos in sequence, generates corresponding fast previews of the videos to be compared and fast previewing key frames to be compared for the videos, and guides the fast previewing key frames to be compared into a key frame comparison program of the cloud computing system.
5. The system of claim 2, wherein the system comprises: a key frame comparison procedure; the cloud computing system firstly introduces the supplement of the sample target key frame circled by the user or the key frame for fast previewing the source video, and if the supplement of the sample target key frame circled by the user exists, the key frame for fast previewing the source video is not introduced; secondly, importing the fast preview key frame to be compared, and comparing the two imported key frames; if the key frame of the sample target can be found in the fast preview key frames to be compared, the video fast preview corresponding to the fast preview key frames to be compared is led into the cloud computing system, and if the key frame of the sample target cannot be found in the fast preview key frames to be compared, the video fast preview and the related video corresponding to the fast preview key frames to be compared are excluded.
6. The system of claim 1, wherein the system comprises: according to the quick preview comparison program, firstly, a cloud computing system imports quick preview of a source video, then imports quick preview of a video to be compared, and starts comparison on the quick preview of the video imported twice by taking a key frame as a joint point; if the continuous synchronous part with the rapid preview of the source video can be found in the rapid preview of the video to be compared, a synchronous time node and a synchronous duration are recorded, the key frame screenshots of the start and the end of the synchronization are recorded, the reference amplitude and the recomposition degree are calculated according to the ratio of the accumulation of the synchronization times and the synchronous duration to the source video and the comparison video, and if the continuous synchronous part cannot be found in the rapid preview of the video to be compared, the corresponding video for rapid preview of the video is excluded.
7. The system according to claim 1, wherein said system comprises: the comparative result data analysis program: and analyzing the data result of the single video and the data result of the batch video, and performing secondary analysis on the related data of the single video to obtain the integral reference range, the adaptation degree and the viewing diffusion fission index.
8. The system of claim 1, wherein the system comprises: in the supervision measures, a user sets thresholds for reference amplitude and adaptation degree in a local system or a cloud platform system, sets supervision treatment measures in each threshold range interval for the thresholds, and obtains suggested feedback of the supervision measures according to the supervision treatment measures.
9. The system of claim 1, wherein the system comprises: and the analysis result statistics output program is used for comparing and calculating the data by the cloud computing system to generate a graphic report which is stored in the cloud platform system and is used for a user to check in the cloud platform system or check after the graphic report is downloaded to a local system.
10. The system of claim 8, wherein the system further comprises: the recommended feedback of the regulatory action includes: ignore, dynamically track, focus on, fission track, reference learning, limit or promote propagation.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080263605A1 (en) * | 2007-04-09 | 2008-10-23 | Hiroshi Mine | Video delivery device, video receiver and key frame delivery method |
| CN101540907A (en) * | 2009-04-28 | 2009-09-23 | 无锡天脉聚源传媒科技有限公司 | Method for auditing safety of internet video |
| CN105872799A (en) * | 2015-12-11 | 2016-08-17 | 乐视移动智能信息技术（北京）有限公司 | Video playing processing method, player and terminal equipment |
| EP3329678A1 (en) * | 2015-07-31 | 2018-06-06 | Forbidden Technologies, PLC | Compressor |
| CN110324729A (en) * | 2019-07-18 | 2019-10-11 | 北京奇艺世纪科技有限公司 | A kind of method, apparatus, electronic equipment and the medium of identification infringement video link |
| CN110705405A (en) * | 2019-09-20 | 2020-01-17 | 阿里巴巴集团控股有限公司 | Target labeling method and device |
| US20210103615A1 (en) * | 2019-10-03 | 2021-04-08 | Adobe Inc. | Adaptive search results for multimedia search queries |
| CN113722543A (en) * | 2021-09-14 | 2021-11-30 | 图灵创智(北京)科技有限公司 | Video similarity comparison method, system and equipment |
| CN114357206A (en) * | 2022-01-13 | 2022-04-15 | 山东女子学院 | Education video color subtitle generation method and system based on semantic analysis |
| CN114626024A (en) * | 2022-05-12 | 2022-06-14 | 北京吉道尔科技有限公司 | Internet infringement video low-consumption detection method and system based on block chain |
| CN114666654A (en) * | 2022-05-20 | 2022-06-24 | 山东浪潮超高清视频产业有限公司 | Comparison method for confirming video image content consistency through rgb color mode |
| CN115348472A (en) * | 2021-05-10 | 2022-11-15 | 北京有竹居网络技术有限公司 | Video identification method and device, readable medium and electronic equipment |
-
2022
- 2022-11-29 CN CN202211503711.1A patent/CN115640422B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080263605A1 (en) * | 2007-04-09 | 2008-10-23 | Hiroshi Mine | Video delivery device, video receiver and key frame delivery method |
| CN101540907A (en) * | 2009-04-28 | 2009-09-23 | 无锡天脉聚源传媒科技有限公司 | Method for auditing safety of internet video |
| EP3329678A1 (en) * | 2015-07-31 | 2018-06-06 | Forbidden Technologies, PLC | Compressor |
| CN105872799A (en) * | 2015-12-11 | 2016-08-17 | 乐视移动智能信息技术（北京）有限公司 | Video playing processing method, player and terminal equipment |
| CN110324729A (en) * | 2019-07-18 | 2019-10-11 | 北京奇艺世纪科技有限公司 | A kind of method, apparatus, electronic equipment and the medium of identification infringement video link |
| CN110705405A (en) * | 2019-09-20 | 2020-01-17 | 阿里巴巴集团控股有限公司 | Target labeling method and device |
| US20210103615A1 (en) * | 2019-10-03 | 2021-04-08 | Adobe Inc. | Adaptive search results for multimedia search queries |
| CN115348472A (en) * | 2021-05-10 | 2022-11-15 | 北京有竹居网络技术有限公司 | Video identification method and device, readable medium and electronic equipment |
| CN113722543A (en) * | 2021-09-14 | 2021-11-30 | 图灵创智(北京)科技有限公司 | Video similarity comparison method, system and equipment |
| CN114357206A (en) * | 2022-01-13 | 2022-04-15 | 山东女子学院 | Education video color subtitle generation method and system based on semantic analysis |
| CN114626024A (en) * | 2022-05-12 | 2022-06-14 | 北京吉道尔科技有限公司 | Internet infringement video low-consumption detection method and system based on block chain |
| CN114666654A (en) * | 2022-05-20 | 2022-06-24 | 山东浪潮超高清视频产业有限公司 | Comparison method for confirming video image content consistency through rgb color mode |
Non-Patent Citations (1)
| Title |
|---|
| 曾凡智;程勇;周燕;: "一种视频时空特征提取算法及其应用研究", 《佛山科学技术学院学报(自然科学版)》, no. 3, pages 21 - 28 * |
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