CN117119255A - Monitoring method, system, equipment and storage medium for illegal video playing - Google Patents

Monitoring method, system, equipment and storage medium for illegal video playing Download PDF

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Publication number
CN117119255A
CN117119255A CN202310693129.4A CN202310693129A CN117119255A CN 117119255 A CN117119255 A CN 117119255A CN 202310693129 A CN202310693129 A CN 202310693129A CN 117119255 A CN117119255 A CN 117119255A
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China
Prior art keywords
video
illegal
image
content
event
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CN202310693129.4A
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Chinese (zh)
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CN117119255B (en
Inventor
刘世章
吴润泽
王全宁
陈楚怡
汪昭辰
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Qingdao Chenyuan Technology Information Co ltd
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Qingdao Chenyuan Technology Information Co ltd
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Priority to CN202310693129.4A priority Critical patent/CN117119255B/en
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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
    • H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
    • H04N21/44204—Monitoring of content usage, e.g. the number of times a movie has been viewed, copied or the amount which has been watched
    • 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
    • H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
    • H04N21/44209—Monitoring of downstream path of the transmission network originating from a server, e.g. bandwidth variations of a wireless network
    • 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
    • H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
    • H04N21/44213—Monitoring of end-user related data
    • 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
    • H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
    • H04N21/44213—Monitoring of end-user related data
    • H04N21/44222—Analytics of user selections, e.g. selection of programs or purchase activity

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Databases & Information Systems (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Social Psychology (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

The application relates to the technical field of video processing, and particularly discloses a monitoring method, a system, equipment and a storage medium for illegal video playing, wherein the method comprises the following steps: constructing a violation video library and a violation image library; acquiring video stream data played in real time, and acquiring a played video event based on the video stream data; performing similarity calculation on the played video event and the illegal video event in the video event information network, and judging whether the played video event is the illegal video event or not; if yes, storing the illegal video clips; if not, carrying out similarity calculation on each content frame in the video event and the illegal image in the image information network, and judging whether the illegal image exists in the content frame in the video event; if yes, storing the illegal video clips in the video stream. The application adopts a small sample autonomous learning technology, effectively monitors the broadcasting condition of illegal video based on the constructed video event information network and image information network, and solves the problems of high manual monitoring cost, low working efficiency and low accuracy.

Description

Monitoring method, system, equipment and storage medium for illegal video playing
Technical Field
The invention relates to the technical field of video processing, in particular to a monitoring method, a system, equipment and a storage medium for illegal video playing.
Background
With the vigorous development of the broadcast television industry, by the end of 2021, the nationwide public market grade or more broadcast television broadcasting institutions start television channels 1200 sets, and 38 sets of education and teaching channels which are started by education television stations at all levels are additionally provided. All levels of broadcast television broadcasting institutions all over the country are approved to make 985 high definition channels, 8 4K channels and 1 8K channels. The department 194 6736 collection was produced year by year 2021 and tv cartoon 78372 minutes. The year round is produced into story film 565, and science, education, recording, animation, and special film 175. The broadcasting time of the 2020 public television program is 1988.31 ten thousand hours.
In such a background, how to monitor video content broadcast in a plurality of television channels and discover illegal videos in time has become a problem to be solved. The existing television play supervision is mainly completed in a manual mode, and the problems of high labor cost, low working efficiency, time consumption and the like exist.
Disclosure of Invention
The embodiment of the invention provides a method, a system, equipment and a storage medium for monitoring illegal video playing, which at least solve the technical problems of low working efficiency, high labor cost and the like in the related technology when monitoring illegal video content.
According to an aspect of the embodiment of the invention, there is provided a method for monitoring illegal video playing, including: constructing a violation video sample library and a violation image sample library, wherein the violation video sample library comprises a violation video event information network, and the violation image sample library comprises a violation image information network; acquiring video stream data played in real time, and obtaining a played video event based on the video stream data, wherein the video event refers to a set of all content frames in a shot, the content frames refer to frames representing shot content, the frames comprise a first frame, a last frame and N middle frames, N is a natural number, the middle frames are obtained when the difference rate is larger than a preset threshold value through difference rate calculation between all sub-frames of the shot except the first frame and the last frame and the previous content frame; performing similarity comparison on the played video event and the illegal video event in the illegal video event information network, and judging whether the played video event is the illegal video or not; if the video is the illegal video, obtaining a first illegal video fragment similar to the content of the illegal video in the illegal video sample library, and storing the first illegal video fragment in the video stream; if the video is not the illegal video, obtaining a played content frame based on the video stream data, carrying out similarity comparison on the played content frame and the illegal image in the illegal image information network, and judging whether the played content frame is the illegal image; and if the illegal image is the illegal image, obtaining an illegal content frame similar to the illegal image content in the illegal image sample library, and storing a second illegal video fragment corresponding to the illegal content frame in the video stream.
According to another aspect of the embodiment of the present invention, there is also provided a monitoring system for illegal video playing, including: the system comprises a violation sample library construction module, a rule-breaking video sample library and a rule-breaking image sample library, wherein the violation video sample library comprises a rule-breaking video event information network, and the rule-breaking image sample library comprises a rule-breaking image information network; the system comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for acquiring video stream data played in real time, and obtaining a played video event based on the video stream data, wherein the video event refers to a set of all content frames in a shot, the content frames refer to frames representing shot contents, the frames comprise a first frame, a tail frame and N middle frames, N is a natural number, the middle frames are obtained when the difference rate is larger than a preset threshold value through calculating the difference rate of all sub-frames of the shot except the first frame and the tail frame and the previous content frame; the video monitoring module is used for carrying out similarity comparison on the played video event and the illegal video event in the illegal video event information network, and judging whether the played video event is the illegal video or not; the first storage module is used for obtaining a first illegal video fragment similar to the illegal video content in the illegal video sample library if the illegal video is the illegal video, and storing the first illegal video fragment in the video stream; the image monitoring module is used for obtaining a played content frame based on the video stream data if the video is not the illegal video, comparing the similarity of the played content frame with the illegal image in the illegal image information network, and judging whether the played content frame is the illegal image; and the second storage module is used for obtaining the illegal content frames similar to the illegal image content in the illegal image sample library if the illegal image is the illegal image, and storing second illegal video clips corresponding to the illegal content frames in the video stream.
According to still another aspect of the embodiments of the present application, there is also provided an electronic device including a memory, and a processor, where the memory stores a computer program, and the processor is configured to execute the method for monitoring illegal video playback by using the computer program.
According to yet another aspect of the embodiments of the present application, there is also provided a computer-readable storage medium having a computer program stored therein, wherein the computer program is configured to perform the above-described method of monitoring illegal video playback when run.
The technical scheme provided by the embodiment of the application can have the following beneficial effects:
according to the monitoring method for illegal video playing provided by the embodiment of the application, on the premise that manual indexes such as keywords and labels or text information are not used, a technical route of small sample autonomous learning is adopted, correlation analysis is performed based on the content of the video completely, a video event information network and an image information network of the illegal video are constructed, a video stream played in real time is input into the video event network and the image information network, and the played illegal video is automatically found. The monitoring method can detect whether each frame of image in the video is illegal, refines each frame of image, is not influenced by processing deformation such as subtitles, audios and watermarks in the video, greatly improves the accuracy of monitoring illegal contents of the video, effectively monitors broadcasting contents of video programs of all channels, and solves the technical problems of high manual monitoring cost, low efficiency and low accuracy in the prior art.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a schematic illustration of an application environment of an alternative method of monitoring offending video playback in accordance with an embodiment of the present application;
FIG. 2 is a schematic illustration of an application environment of another alternative method of monitoring offending video playback in accordance with an embodiment of the present application;
FIG. 3 is a flow chart of an alternative method of monitoring for offending video playback in accordance with an embodiment of the present application;
FIG. 4 is a schematic diagram of a video event information space provided in accordance with an embodiment of the present application;
FIG. 5 is a schematic diagram of an image information space provided in accordance with an embodiment of the present application;
FIG. 6 is a schematic diagram of a method for constructing a violation sample base according to an embodiment of the present application;
FIG. 7 is a method for monitoring offensive video provided in accordance with an embodiment of the present application;
FIG. 8 is a method for monitoring an offending image provided in accordance with an embodiment of the present application;
FIG. 9 is a video event monitoring flow chart based on a video event information network provided in accordance with an embodiment of the present application;
FIG. 10 is a flow chart of image monitoring based on an image information network according to an embodiment of the present application;
FIG. 11 is a schematic diagram of a monitoring system for illegal video playback according to an embodiment of the present application;
FIG. 12 is a schematic diagram of an alternative monitoring system for offending video playback in accordance with an embodiment of the present application;
fig. 13 is a schematic structural view of an alternative electronic device according to an embodiment of the present application.
Detailed Description
In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
According to an aspect of the embodiment of the present invention, a method for monitoring illegal video playing is provided, and as an alternative implementation manner, the method for monitoring illegal video playing may be, but is not limited to, applied to an application environment as shown in fig. 1. The application environment comprises the following steps: a terminal device 102, a network 104 and a server 106 which interact with a user in a man-machine manner. Human-machine interaction can be performed between the user 108 and the terminal device 102, and a monitoring application program for illegal video playing runs in the terminal device 102. The terminal device 102 includes a man-machine interaction screen 1022, a processor 1024 and a memory 1026. The man-machine interaction screen 1022 is used for displaying the broadcasted video; the processor 1024 is used to obtain the video that is played out. The memory 1026 is used to store the video that is played out as described above.
In addition, the server 106 includes a database 1062 and a processing engine 1064, and the database 1062 is used to store the video played out as described above. The processing engine 1064 is configured to: constructing a violation video sample library and a violation image sample library, wherein the violation video sample library comprises a violation video event information network, and the violation image sample library comprises a violation image information network; acquiring video stream data played in real time, and obtaining a played video event based on the video stream data, wherein the video event refers to a set of all content frames in a shot, the content frames refer to frames representing shot content, the frames comprise a first frame, a last frame and N middle frames, N is a natural number, the middle frames are obtained when the difference rate is larger than a preset threshold value through calculating the difference rate of all sub-frames of the shot except the first frame and the last frame and the previous content frame; the method comprises the steps of carrying out similarity comparison on a played video event and a violation video event in a violation video event information network, and judging whether the played video event is a violation video or not; if the video is the illegal video, obtaining a first illegal video fragment similar to the content of the illegal video in the illegal video sample library, and storing the first illegal video fragment in the video stream; if the video is not the illegal video, obtaining a played content frame based on the video stream data, carrying out similarity comparison on the played content frame and the illegal image in the illegal image information network, and judging whether the played content frame is the illegal image; and if the video is the illegal image, obtaining an illegal content frame similar to the content of the illegal image in the illegal image sample library, and storing a second illegal video fragment corresponding to the illegal content frame in the video stream.
In one or more embodiments, the method for monitoring illegal video playback according to the present application may be applied to the application environment shown in fig. 2. As shown in fig. 2, a human-machine interaction may be performed between a user 202 and a user device 204. The user device 204 includes a memory 206 and a processor 208. The user equipment 204 in this embodiment may, but is not limited to, monitor the video broadcast situation with reference to performing the operations performed by the terminal equipment 102.
Optionally, the terminal device 102 and the user device 204 include, but are not limited to, a mobile phone, a tablet computer, a notebook computer, a PC, a vehicle-mounted electronic device, a wearable device, and the like, and the network 104 may include, but is not limited to, a wireless network or a wired network. Wherein the wireless network comprises: WIFI and other networks that enable wireless communications. The wired network may include, but is not limited to: wide area network, metropolitan area network, local area network. The server 106 may include, but is not limited to, any hardware device that may perform calculations. The server may be a single server, a server cluster composed of a plurality of servers, or a cloud server. The above is merely an example, and is not limited in any way in the present embodiment.
The following describes in detail a method for monitoring illegal video playing according to an embodiment of the present application with reference to fig. 3, and as shown in fig. 3, the method mainly includes the following steps:
s301, constructing a violation video sample library and a violation image sample library, wherein the violation video sample library comprises a violation video event information network, and the violation image sample library comprises a violation image information network.
In one exemplary scenario, with television channels or video playing software, the video being played involves illegal content, such as false advertisements, forbidden movies, false news, etc., so that the illegal content of the video being played should be effectively monitored, the video playing quality is ensured, and the video playing environment is maintained.
First, a library of offending video samples is constructed. In an alternative embodiment, constructing a library of offending video samples includes: and obtaining a violation video sample to be monitored, and preprocessing the violation video sample to obtain a normalized video. The method comprises the steps of preprocessing the illegal video samples, including but not limited to video frame decomposition, picture-in-picture image extraction, frame removal and the like of the images in the video, and simultaneously carrying out normalized conversion of resolution, amplitude-shape ratio, color space and the like on the images of the video, so that the obtained normalized video has the video with the same dimension, and is convenient for granulating.
Further, the normalized video is subjected to granulation processing to obtain a video event sequence, wherein the video event sequence comprises at least one video event, and the video event refers to a set of all content frames in one lens.
In this embodiment, the granulating the normalized video to obtain a video event sequence includes: and carrying out shot monitoring according to the frame sequences in the normalized video to obtain shot sequences, wherein the shot sequences comprise at least one shot, extracting content frames from the video frame sequences of each shot in the shot sequences to obtain the content frame sequences of each shot, and obtaining a video event sequence according to the shot sequences and the content frame sequences.
In this embodiment, the granulating process refers to performing shot segmentation on a video to obtain a granulating structure of the video, where the principle of obtaining the granulating structure is as follows: the video content is composed of continuous frame sequences, the continuous frame sequences can be divided into a plurality of groups according to the continuity of the video content, shot monitoring is carried out according to the frame sequences, each group of continuous frame sequences is a shot, the shot sequences comprise at least one shot, a small number of frames are selected from the continuous frame sequences to represent the shot content by analyzing the difference of the content in the video shots, the frames are content frames, namely, the video frame sequences of each shot in the shot sequences are subjected to content frame extraction to obtain the content frame sequences of each shot, and then the video event sequences are obtained according to the shot sequences and the content frame sequences. Wherein, the content frames at least comprise the first and last two frames (shot frames) of the shot, so the content frame number of one shot is more than or equal to 2.
In this embodiment, the video event sequence includes at least one video event, where the video event refers to a set of all content frames in a shot, the content frames include a first frame, a last frame, and N intermediate frames, N is a natural number, and the intermediate frames are obtained when the difference rate is greater than a preset threshold by performing difference rate calculation on all subframes of the shot except for the first frame and the last frame and the previous content frame.
Further, analyzing and calculating characteristic data of each content frame of the video event, and obtaining the characteristic data of the video event according to the characteristic data of the content frame.
In this embodiment, the feature data of the video event includes the number of content frames of the video event and the feature matrix of the content frames of the video event, and the feature matrix of the content frames of the video event includes the feature matrix of each content frame included in the video event. The feature matrix of each content frame may be obtained according to the uniformity lbp feature of the content frame, which may better reflect the content feature of the video event, and in an alternative example, the feature matrix of the content frame may be obtained according to other features of the content frame, such as a histogram feature, a sift feature, a hog feature, and a haar feature, which are not listed herein.
In this embodiment, analysis and calculation are performed on a content frame of a video event to obtain feature data of the video event, including: obtaining the number of the content frames of the video event according to the number of the frames of the content frames in the content frame set of the video event, and obtaining the feature vector of the video event according to the feature matrix of each content frame in the content frame set of the video event.
And finally, constructing an illegal video event information network in the video event information space according to the characteristic data of the video event. The video event information network is a forest structure constructed based on a multi-level tree set based on a video event information space, the video event information space is a multi-dimensional vector space in which video event feature vectors are located, the video event feature vectors are obtained by calculating after feature matrixes are extracted from a content frame set under the same coordinate system, the multi-level tree comprises root nodes and child nodes, the difference rate between video events corresponding to any two root nodes is larger than a preset threshold value, and the difference rate between the child nodes of each root node and the video events corresponding to the root nodes is smaller than or equal to the preset threshold value.
The above embodiment can know that the video event information space is a multidimensional vector space in which the video event feature vector is located and has a regional characteristic, so that a forest structure can be constructed based on a multi-level tree set to form a illegal video event information network, that is, the video event information network is a forest structure constructed based on the multi-level tree set based on the video event information space.
FIG. 4 is a schematic diagram of a video event information space provided in accordance with an embodiment of the present application; as shown in fig. 4, the tree structure may be divided into two levels according to the relationship between the regions in the video event information space, where the first level is the center of the circle corresponding to the root node corresponding to each spatial region, and the second level is the non-center point in the sub-node corresponding to each spatial region. If the space region is subdivided into multiple sub-regions, the tree structure will also generate corresponding multi-level sub-nodes, where the number of levels of the tree structure corresponds to the number of levels of the space region in the information space, and in this embodiment, a 2-level tree structure is described as an example.
As shown in fig. 4, a plurality of multi-level tree structures can be obtained according to the video event information space, the multi-level tree includes a root node and sub-nodes, a forest structure constructed based on a multi-level tree set formed by the plurality of multi-level tree structures is a video event information network, each sub-node in the video event information network at least belongs to 1 root node, and no sub-node exists under the root node. The difference rate between the video events corresponding to any two root nodes is larger than a preset threshold, and the difference rate between the child node of each root node and the video event corresponding to the root node is smaller than or equal to the preset threshold.
Based on the video event information space and the video event information network, the video event information network of the present embodiment is constructed based on the video event, so that after the feature data of the video event is obtained, the video event information network is constructed in the video event information space according to the feature data of the video event. As can be seen from the association relationship between the tree structures of the video event information, the video events in the video event information network have the association relationship based on the similarity of the video events because the video events of the child nodes are similar to the video events of the root nodes of the child nodes and the video events corresponding to the different root nodes are dissimilar.
And finally, storing the video information, the shot information, the content frame information and the network of the illegal video event information of the illegal video sample into an illegal video sample library. And obtaining a constructed illegal video sample library.
The embodiment of the application not only can monitor video events, but also can be granulated to the frame image level for monitoring. Therefore, a violation image sample library needs to be constructed.
In the embodiment of the application, constructing a violation image sample library comprises the following steps: and obtaining a violation video sample to be monitored, and extracting a content frame of the violation video sample.
The application can granulate to the frame level, therefore, granulate the obtained offence video sample to be monitored, extract the content frame in the video, the video content is composed of continuous frame sequences, the continuous frame sequences can be divided into a plurality of groups according to the continuity of the video content, the lens monitoring is carried out according to the frame sequences, each group of continuous frame sequences is a lens, and a small number of frames are selected from the continuous frame sequences to represent the content of the lens by analyzing the difference of the content in the video lens, and the frames are the content frames. The content frames comprise a first frame, a last frame and N intermediate frames, wherein N is a natural number, and the intermediate frames are obtained when the difference rate is larger than a preset threshold value by carrying out difference rate calculation on all sub-frames of a shot except the first frame and the last frame and the previous content frame.
Further, a violation image sample to be monitored is obtained, and the violation image to be monitored can be extracted from the violation video, and can be obtained from other channels or specified by a user. For example, a false news image is a offending image, which can be added directly to the offending image information network.
Further, the content frames of the illegal video samples and/or the illegal image samples are normalized to obtain normalized images. The method comprises the steps of, but is not limited to, normalizing the monitored violation images in the amplitude-to-shape ratio, resolution and color space, so that each violation image has the same image dimension, the content of a large number of images is conveniently analyzed under the same coordinate system, similarity analysis among different image contents is conveniently performed according to pixels of the images, and the analysis rate of the image contents is accelerated.
Further, feature data of the normalized image are calculated, and a illegal image information network is constructed in an image information space according to the feature data of the normalized image. The image information space is a multidimensional vector space in which image feature vectors are located, the image feature vectors are obtained by calculating after feature matrixes are extracted from images under the same coordinate system, the image information network is a forest structure which is constructed based on a multi-level tree set based on the image information space, the multi-level tree comprises root nodes and child nodes, the difference rate between images corresponding to any two root nodes is larger than a preset threshold, and the difference rate between the child nodes of each root node and the images corresponding to the root nodes is smaller than or equal to the preset threshold.
Specifically, firstly, the image features of the normalized image are calculated, and the image features include, but are not limited to, image features composed of the UniformLBP features, and the UniformLBP features have good sensitivity to image texture changes, so that the UniformLBP features of the image are adopted as the image features, and the content features of the image can be reflected better.
In an alternative example, the image features may also be other image features, such as histogram features, sift features, hog features, haar features, etc., which are not listed here.
Further, a network of offending image information is built in the image information space according to the feature data of the normalized image, and fig. 5 is a schematic diagram of an image information space provided according to an embodiment of the present application. As shown in fig. 5, the tree structure may be divided into two stages according to the relationship between the regions in the image information space, where the first stage is the center of the circle of the space region corresponding to the root node, and the second stage is the non-center point of the space region corresponding to the child node. If the space region is subdivided into multiple sub-regions, the tree structure will also generate corresponding multi-level sub-nodes, where the number of levels of the tree structure corresponds to the number of levels of the space region in the information space, and in this embodiment, a 2-level tree structure is described as an example.
As shown in fig. 5, a plurality of multi-level tree structures can be obtained according to the image information space, the multi-level tree includes a root node and sub-nodes, a forest structure constructed based on a multi-level tree set formed by the plurality of multi-level tree structures is an image information network, each sub-node in the image information network at least belongs to 1 root node, and no sub-node exists under the root node.
Based on the image information space and the image information network, the image information network of the present embodiment is constructed based on the image, and therefore, the image information network is constructed in the image information space with the offending image as the target node after analyzing the pixel content of the normalized image to obtain the image characteristics. Because the images of the child nodes are similar to the root node, and the images corresponding to the root node are dissimilar, the images in the image information network have an association relationship based on the image similarity.
And finally, storing the content frame information and/or the violation image information of the violation video and the violation image information network into a violation image sample library to obtain a constructed violation image sample library.
Fig. 6 is a schematic diagram of a method for constructing a violation sample base, where as shown in fig. 6, a violation video sample to be monitored is obtained, pre-processing such as frame decomposition and normalization is performed on the violation video sample, lens segmentation and content frame extraction are performed to obtain a video event, a violation video event information network is constructed, and the video event information network and the video event information are stored in the violation video base; further, according to the extracted content frames and the obtained illegal images, an illegal image information network is constructed, and the content frame information, the image information and the image information network are stored in an illegal image library. Obtaining a violation sample library according to the violation image library and the violation video library.
S302, acquiring video stream data played in real time, and obtaining a played video event based on the video stream data, wherein the video event refers to a set of all content frames in a shot, the content frames refer to frames representing shot content, the frames comprise a first frame, a last frame and N middle frames, N is a natural number, the middle frames are obtained when the difference rate is larger than a preset threshold value through difference rate calculation between all sub-frames of the shot except the first frame and the last frame and the previous content frame.
In one possible implementation manner, the content of the played television program is monitored, video stream data played in real time is obtained, the video stream data is deframed, and the video frames are subjected to normalization processing such as resolution, amplitude-shape ratio, color space and the like.
Further, the normalized video is subjected to granulation processing to obtain a video event sequence, and the video event sequence comprises at least one video event, wherein the video event refers to a set of all content frames in one lens.
And similar to the illegal video to be monitored, analyzing and calculating the content frames of the video event to obtain the characteristic data of the video event. Comprising the following steps: obtaining the number of the content frames of the video event according to the number of the frames of the content frames in the content frame set of the video event, and obtaining the feature vector of the video event according to the feature matrix of each content frame in the content frame set of the video event.
S303, comparing the similarity of the played video event with the illegal video event in the illegal video event information network, and judging whether the played video event is the illegal video.
Specifically, inputting the played video event into a illegal video event information network, and calculating the similarity ratio of the played video event to the video event corresponding to each root node in the video event information network; if the similarity is larger than a preset similarity threshold, determining that the video event corresponding to the current root node is similar to the played video event, and adding the video event corresponding to all root nodes with the similarity larger than the preset similarity threshold into a result set; and obtaining all the child nodes under the root node with the similarity greater than the preset similarity threshold, calculating the similarity of the played video event and the video event corresponding to the child node, and adding the video event corresponding to all the child nodes with the similarity greater than the preset similarity threshold into a result set. When the result set has illegal video events similar to the played video events, determining that the played video events are illegal videos.
Fig. 7 is a schematic diagram of a method for monitoring an offending video according to an embodiment of the present application, as shown in fig. 7, in which played video stream data is obtained, pre-processing such as frame decomposition and normalization is performed on the video stream, lens segmentation is performed, a content frame is extracted, video event feature data is obtained according to the content frame feature data, the video event feature data is input into an offending video event information network in an offending video library, event monitoring is performed, a monitoring result is obtained, and the monitoring result is saved and reported.
Specifically, fig. 9 is a video event monitoring flowchart based on a video event information network, and as shown in fig. 9, the implementation process of the method for monitoring an offensive video event based on an offensive video event information network is as follows, where the video event E is known to be played:
step 1: traversing root nodes in a video event information network, and setting the video event information of the current root node as E r ；
Step 2: calculation of E and E r Similarity Sim of (a);
step 3: if meeting the condition that Sim is not less than Sim min (Sim min Preset similarity threshold) then E and E r Similarly, will E r Adding to a result set; otherwise, turning to step 8;
step 4: traversal E r Setting the video event of the current child node as E for all the child nodes c ；
Step 5: calculation of E and E c Similarity Sim of (a);
step 6: will E c Adding to a result set;
step 7: repeating the steps 4-6 until the sub-node traversal is finished;
step 8: repeating the steps 1-7 until the root node traversal is finished;
step 9: and returning a result set.
When the video event in the video stream is similar to the illegal video event in the network, a first video segment in the played video stream similar to the illegal video content to be monitored can be determined according to the similar video event. According to the scheme provided by the application, the illegal content of video playing can be rapidly found on the premise that the manual indexing or the text information such as keywords, labels and the like is not used.
And S304, if the video is the illegal video, obtaining a first illegal video fragment similar to the content of the illegal video in the illegal video sample library, and storing the first illegal video fragment in the video stream.
If the illegal video is monitored through the illegal video event information network, a first illegal video fragment similar to the content of the illegal video in the illegal video sample library is obtained, and the first illegal video fragment in the video stream is stored.
In an alternative embodiment, after saving the first offending video segment in the video stream, further comprising: recording first violation information of a first violation video clip, the first violation information comprising: play duration information, play start-stop time information, illegal video event information, such as content frame information, shot information, etc., of the illegal video event, and play channel information; and reporting the first violation information to the user terminal.
In one embodiment, the first violation information is sent to a terminal device such as a computer, a mobile phone and the like of the user for the user to review. For example, the violation report may be sent in the form of a mail, or may be sent in other forms, and embodiments of the present application are not particularly limited.
And S305, if the video is not the illegal video, obtaining a played content frame based on the video stream data, comparing the similarity of the played content frame with the illegal image in the illegal image information network, and judging whether the played content frame is the illegal image.
In one embodiment, if the illegal video cannot be monitored through the video event information network, the monitoring is performed by using the pre-constructed image information network, and whether the illegal video frame exists is judged. The accuracy of monitoring can be greatly improved.
Specifically, the method comprises the steps of obtaining played video stream data, performing frame decomposition on the video stream data, extracting content frames in the video stream data, wherein the content frames refer to frames representing shot content, the frames comprise a first frame, a last frame and N middle frames, N is a natural number, the middle frames are obtained when the difference rate is larger than a preset threshold value through difference rate calculation between all sub-frames of a shot except the first frame and the last frame and the previous content frame.
Further, inputting the extracted content frames into an image information network, and calculating the similarity of the content frames and images corresponding to each root node in the image information network for each content frame in the video event; if the similarity is larger than a preset similarity threshold, determining that the image corresponding to the current root node is similar to the played content frame, and adding the images corresponding to all root nodes with the similarity larger than the preset similarity threshold into a result set; obtaining all sub-nodes under the root node with the similarity greater than a preset similarity threshold, calculating the similarity of the played content frame and the images corresponding to the sub-nodes, and adding the images corresponding to the sub-nodes with the similarity greater than the preset similarity threshold into a result set; when the result set has illegal images similar to the content frames, the played content frames are determined to be the illegal images.
Fig. 8 is a schematic diagram of a method for monitoring illegal images according to an embodiment of the present application, as shown in fig. 8, in which played video stream data is obtained, pre-processing such as frame decomposition and normalization is performed on the video stream data, and lens segmentation and extraction are performed to obtain content frame information of a played video, the played content frame is input into a network of illegal image information in a illegal image library, image monitoring is performed to obtain a monitoring result, and the monitoring result is obtained, stored and reported.
Fig. 10 is a diagram of an image monitoring method based on an image information network according to an embodiment of the present application, as shown in fig. 10, the image information F is known, and the implementation procedure of the image monitoring method based on an image information network is as follows:
step 1: traversing root nodes in the image information network, and setting the image information of the current root node as F r ；
Step 2: calculating F and F r Similarity Sim of (a);
step 3: if meeting the condition that Sim is not less than Sim min (Sim min Preset threshold value) then F and F r Similarly, F is r Adding to a result set; otherwise, turning to step 8;
step 4: traversal F r Setting the image information of the current sub-node as F for all the sub-nodes c ；
Step 5: calculating F and F c Similarity Sim of (a);
step 6: will F c Adding to a result set;
step 7: repeating the steps 4-6 until the sub-node traversal is finished;
step 8: repeating the steps 1-7 until the root node traversal is finished;
step 9: and returning a result set.
When the content frames in the video stream are similar to the illegal images in the network, the illegal images similar to the content of the illegal images to be monitored in the video stream can be determined according to the similar illegal images, so that frame-level monitoring can be realized, and the accuracy of illegal video monitoring is improved.
And S306, if the video is the illegal image, obtaining an illegal content frame similar to the content of the illegal image in the illegal image sample library, and storing a second illegal video clip corresponding to the illegal content frame in the video stream.
In the embodiment of the application, if the illegal content frame is monitored, the playing time information of the illegal content frame in the video stream is obtained, the video with the preset duration is intercepted forwards and the video with the preset duration is intercepted backwards by taking the playing time corresponding to the illegal content frame as a midpoint, and the second illegal video segment is obtained. For example, if the playback time corresponding to the offending content frame is 17:10:20, then 17:09:20-17:11: the video between 20 is saved as a second video clip. Specifically, the intercepting duration can be set according to actual conditions.
In an alternative embodiment, after storing the second offending video segment corresponding to the offending content frame in the video stream, the method further includes: recording second violation information of a second violation video clip, the second violation information comprising: playing time length information, playing start-stop time information, time information of illegal content frames, illegal image sample information and playing channel information; and reporting the second violation information to the user terminal.
In one embodiment, the second violation information is sent to a terminal device such as a computer, a mobile phone, etc. of the user for the user to review. For example, the violation report may be sent in the form of a mail, or may be sent in other forms, and embodiments of the present application are not particularly limited.
Fig. 11 is a schematic diagram of a monitoring system for illegal video playing according to an embodiment of the present application, and as shown in fig. 11, a system logic framework design is divided into four layers of an infrastructure layer, an information production layer, a platform technology layer and an application display layer.
The infrastructure layer is the basis for the reliable, stable and efficient operation of the whole system, and comprises an operating system, application software, hardware for data storage and dynamic management service and a communication facility.
The information production layer stores, normalizes and granulates the access video, carries out small sample autonomous learning on the video content, realizes the analysis of the video content and provides data support for system application.
The platform technology layer provides an adaptive service interface for diversified applications through image feature and event feature analysis.
The application presentation layer comprises resource allocation and provides content frames after system analysis processing.
According to the monitoring method for illegal video playing provided by the embodiment of the application, on the premise that manual indexes such as keywords and labels or text information are not used, a technical route of small sample autonomous learning is adopted, correlation analysis is performed based on the content of the video completely, a video event information network and an image information network of the illegal video are constructed, a video stream played in real time is input into the video event network and the image information network, and the played illegal video is automatically found. The monitoring method can detect whether each frame of image in the video is illegal, refines each frame of image, is not influenced by processing deformation such as subtitles, audios and watermarks in the video, greatly improves the accuracy of monitoring illegal contents of the video, effectively monitors broadcasting contents of video programs of all channels, and solves the technical problems of high manual monitoring cost, low efficiency and low accuracy in the prior art.
According to another aspect of the embodiment of the invention, a monitoring system for illegal video playing is also provided, wherein the monitoring system is used for implementing the monitoring method for illegal video playing. As shown in fig. 12, the system includes:
the violation sample library construction module 1201 is used for constructing a violation video sample library and a violation image sample library, wherein the violation video sample library comprises a violation video event information network, and the violation image sample library comprises a violation image information network;
the obtaining module 1202 is configured to obtain video stream data that is played in real time, obtain a video event that is played based on the video stream data, where the video event refers to a set of all content frames in a shot, the content frames refer to frames that represent shot content, including a first frame, a last frame, and N intermediate frames, where N is a natural number, and the intermediate frames are obtained when the difference rate is greater than a preset threshold by performing difference rate calculation on all subframes of a shot except the first frame and the last frame and a previous content frame;
the video monitoring module 1203 is configured to compare the similarity of the played video event with the illegal video event in the illegal video event information network, and determine whether the played video event is the illegal video;
The first storage module 1204 is configured to obtain a first offending video segment similar to the offending video content in the offending video sample library if the offending video is the offending video, and store the first offending video segment in the video stream;
the image monitoring module 1205 is configured to obtain a played content frame based on the video stream data if the played content frame is not the illegal video, compare the similarity between the played content frame and the illegal image in the illegal image information network, and determine whether the played content frame is the illegal image;
the second storage module 1206 is configured to obtain a violation content frame similar to the violation image content in the violation image sample library if the violation image is the violation image, and store a second violation video clip corresponding to the violation content frame in the video stream.
It should be noted that, when the monitoring system for illegal video playing provided in the foregoing embodiment performs the monitoring method for illegal video playing, only the division of the foregoing functional modules is used for illustration, and in practical application, the foregoing functional allocation may be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to complete all or part of the functions described above. In addition, the monitoring system for illegal video playing provided in the above embodiment and the monitoring method embodiment for illegal video playing belong to the same concept, which embody detailed implementation process see method embodiment, and are not described herein again.
According to still another aspect of the embodiment of the present invention, there is further provided an electronic device for implementing the method for monitoring illegal video playing, where the electronic device may be a terminal device or a server as shown in fig. 13. The present embodiment is described taking the electronic device as an example. As shown in fig. 13, the electronic device comprises a memory 1305 and a processor 1303, the memory 1305 storing a computer program, the processor 1303 being arranged to execute the steps of any of the method embodiments described above by means of the computer program.
Alternatively, in this embodiment, the electronic device may be located in at least one network device of a plurality of network devices of the computer network.
Alternatively, it will be understood by those skilled in the art that the structure shown in fig. 13 is only schematic, and the electronic device may also be a smart phone (such as an Android mobile phone, an iOS mobile phone, etc.), a tablet computer, a palm computer, and a terminal device such as a mobile internet device (Mobile Internet Devices, MID), a PAD, etc. Fig. 13 is not limited to the structure of the electronic device and the electronic apparatus described above. For example, the electronics can also include more or fewer components (e.g., network interfaces, etc.) than shown in fig. 13, or have a different configuration than shown in fig. 13.
The memory 1305 may be used to store software programs and modules, such as program instructions/modules corresponding to the method and apparatus for monitoring illegal video playing in the embodiment of the present invention, and the processor 1303 executes the software programs and modules stored in the memory 1305 to perform various functional applications and data processing, that is, implement the method for monitoring illegal video playing. The memory 1305 may include high-speed random access memory, but may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid state memory. In some examples, the memory 1305 may further include memory located remotely from the processor 1303, which may be connected to the terminal through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof. The memory 1305 may be used for storing information such as holographic video, among other things. As an example, as shown in fig. 13, the memory 1305 may include, but is not limited to, an offending sample library construction module 1201, an acquisition module 1202, a video monitoring module 1203, a first storage module 1204, an image monitoring module 1205, and a second storage module 1206 in the monitoring system including the offending video playing.
In addition, other module units in the monitoring system for illegal video playing may be included, but are not limited to, and are not described in detail in this example.
Optionally, the transmission device 1304 is used to receive or transmit data via a network. Specific examples of the network described above may include wired networks and wireless networks. In one example, the transmission device 1304 includes a network adapter (Network Interface Controller, NIC) that can connect to other network devices and routers via a network cable to communicate with the internet or a local area network. In one example, the transmission device 1304 is a Radio Frequency (RF) module, which is configured to communicate wirelessly with the internet.
In addition, the electronic device further includes: a display 1301 for displaying the video data; and a connection bus 1302 for connecting the respective module components in the above-described electronic device.
According to one aspect of the present application, there is provided a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The computer instructions are read from a computer readable storage medium by a processor of a computer device, which computer instructions are executed by the processor, causing the computer device to perform the method of monitoring video playback for video violations described above, wherein the computer program is arranged to perform the steps of any of the method embodiments described above when run.
Alternatively, in this embodiment, it will be understood by those skilled in the art that all or part of the steps in the methods of the above embodiments may be performed by a program for instructing a terminal device to execute the steps, where the program may be stored in a computer readable storage medium, and the storage medium may include: flash disk, read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), magnetic or optical disk, and the like.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
The integrated units in the above embodiments may be stored in the above-described computer-readable storage medium if implemented in the form of software functional units and sold or used as separate products. Based on such understanding, the technical solution of the present invention may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing one or more computer devices (which may be personal computers, servers or network devices, etc.) to perform all or part of the steps of the method of the various embodiments of the present invention.
In several embodiments provided by the present application, it should be understood that the disclosed client may be implemented in other manners. The system embodiments described above are merely exemplary, such as division of units, merely a logic function division, and other division manners may be implemented in practice, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The foregoing is merely a preferred embodiment of the present application and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present application, which are intended to be comprehended within the scope of the present application.

Claims (10)

1. The method for monitoring illegal video playing is characterized by comprising the following steps:
constructing a violation video sample library and a violation image sample library, wherein the violation video sample library comprises a violation video event information network, and the violation image sample library comprises a violation image information network;
acquiring video stream data played in real time, and obtaining a played video event based on the video stream data, wherein the video event refers to a set of all content frames in a shot, the content frames refer to frames representing shot content, the frames comprise a first frame, a last frame and N middle frames, N is a natural number, the middle frames are obtained when the difference rate is larger than a preset threshold value through difference rate calculation between all sub-frames of the shot except the first frame and the last frame and the previous content frame;
performing similarity comparison on the played video event and the illegal video event in the illegal video event information network, and judging whether the played video event is the illegal video or not;
if the video is the illegal video, obtaining a first illegal video fragment similar to the content of the illegal video in the illegal video sample library, and storing the first illegal video fragment in the video stream;
If the video is not the illegal video, obtaining a played content frame based on the video stream data, carrying out similarity comparison on the played content frame and the illegal image in the illegal image information network, and judging whether the played content frame is the illegal image;
and if the illegal image is the illegal image, obtaining an illegal content frame similar to the illegal image content in the illegal image sample library, and storing a second illegal video fragment corresponding to the illegal content frame in the video stream.
2. The method of claim 1, further comprising, after saving the first offending video segment in the video stream:
recording first violation information of the first violation video clip, the first violation information comprising: playing time length information, playing start-stop time information, illegal video event information and playing channel information;
and reporting the first violation information to a user terminal.
3. The method of claim 1, further comprising, after storing the second offending video segment corresponding to the offending content frame in the video stream:
recording second violation information of the second violation video clip, the second violation information comprising: playing time length information, playing start-stop time information, time information of illegal content frames, illegal image sample information and playing channel information;
And reporting the second violation information to the user terminal.
4. The method of claim 1, wherein constructing the library of offending video samples comprises:
obtaining a violation video sample to be monitored, and preprocessing the violation video sample to obtain a normalized video;
granulating the normalized video to obtain a video event sequence, wherein the video event sequence comprises at least one video event, and the video event refers to a set of all content frames in one lens;
analyzing and calculating characteristic data of each content frame of the video event, and obtaining the characteristic data of the video event according to the characteristic data of the content frame;
according to the feature data of the video event, an illegal video event information network is constructed in a video event information space, the video event information network is a forest structure constructed based on a multi-level tree set based on the video event information space, the video event information space is a multi-dimensional vector space in which video event feature vectors are located, the video event feature vectors are obtained by calculating after feature matrixes are extracted from a content frame set under the same coordinate system, the multi-level tree comprises root nodes and child nodes, the difference rate between any two video events corresponding to the root nodes is larger than a preset threshold value, and the difference rate between the child node of each root node and the video event corresponding to the root node is smaller than or equal to the preset threshold value;
And storing the video information, the shot information, the content frame information and the network of the illegal video event information of the illegal video sample into the illegal video sample library.
5. The method of claim 1, wherein constructing a library of offending image samples comprises:
obtaining a violation video sample to be monitored, and extracting a content frame of the violation video sample;
obtaining a violation image sample to be monitored;
normalizing the content frames of the illegal video samples and/or the illegal image samples to obtain normalized images;
calculating feature data of the normalized image, and constructing an image information network in an image information space according to the feature data of the normalized image, wherein the image information space refers to a multidimensional vector space in which image feature vectors are located, the image feature vectors are obtained by calculating after feature matrixes are extracted from images under the same coordinate system, the image information network is a forest structure which is constructed based on a multistage tree set based on the image information space, the multistage tree comprises root nodes and sub-nodes, the difference rate between any two images corresponding to the root nodes is larger than a preset threshold, and the difference rate between the sub-node of each root node and the image corresponding to the root node is smaller than or equal to the preset threshold;
And storing the content frame information and/or the illegal image information of the illegal video and the illegal image information network into the illegal image sample library.
6. The method of claim 1, wherein comparing the played video event with the offending video event in the offending video event information network to determine whether the played video event is an offending video, comprising:
calculating the similarity between the played video event and the video event corresponding to each root node in the video event information network;
if the similarity is larger than a preset similarity threshold, determining that the video event corresponding to the current root node is similar to the played video event, and adding the video event corresponding to all root nodes with similarity larger than the preset similarity threshold into a result set;
obtaining all the child nodes under the root node with the similarity greater than a preset similarity threshold, calculating the similarity of the played video event and the video event corresponding to the child node, and adding the video event corresponding to all the child nodes into a result set;
and when the result set has illegal video events similar to the played video events, determining that the played video events are illegal videos.
7. The method of claim 1, wherein comparing the played content frame with the offending image in the offending image information network to determine whether the played content frame is an offending image comprises:
calculating the similarity of the content frames and the images corresponding to each root node in the image information network for each content frame in the video event;
if the similarity is larger than a preset similarity threshold, determining that the image corresponding to the current root node is similar to the played content frame, and adding the images corresponding to all root nodes with the similarity larger than the preset similarity threshold into a result set;
obtaining all sub-nodes under the root node with the similarity greater than a preset similarity threshold, calculating the similarity of the played content frame and the images corresponding to the sub-nodes, and adding the images corresponding to all the sub-nodes into a result set;
and when the illegal images similar to the content frames exist in the result set, determining that the played content frames are illegal images.
8. A monitoring system for illegal video playback, comprising:
the system comprises a violation sample library construction module, a rule-breaking video sample library and a rule-breaking image sample library, wherein the violation video sample library comprises a rule-breaking video event information network, and the rule-breaking image sample library comprises a rule-breaking image information network;
The system comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for acquiring video stream data played in real time, and obtaining a played video event based on the video stream data, wherein the video event refers to a set of all content frames in a shot, the content frames refer to frames representing shot contents, the frames comprise a first frame, a tail frame and N middle frames, N is a natural number, the middle frames are obtained when the difference rate is larger than a preset threshold value through calculating the difference rate of all sub-frames of the shot except the first frame and the tail frame and the previous content frame;
the video monitoring module is used for carrying out similarity comparison on the played video event and the illegal video event in the illegal video event information network, and judging whether the played video event is the illegal video or not;
the first storage module is used for obtaining a first illegal video fragment similar to the illegal video content in the illegal video sample library if the illegal video is the illegal video, and storing the first illegal video fragment in the video stream;
the image monitoring module is used for obtaining a played content frame based on the video stream data if the video is not the illegal video, comparing the similarity of the played content frame with the illegal image in the illegal image information network, and judging whether the played content frame is the illegal image;
And the second storage module is used for obtaining the illegal content frames similar to the illegal image content in the illegal image sample library if the illegal image is the illegal image, and storing second illegal video clips corresponding to the illegal content frames in the video stream.
9. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method according to any of the claims 1 to 7 by means of the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a stored program, wherein the program, when run, performs the method of any one of claims 1 to 7.
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