Video auditing method and device, auditing server and storage medium

A server and video technology, applied in video data retrieval, neural learning methods, video data clustering/classification, etc., can solve misjudgments or missed judgments, cannot accurately review video violation types, and multiple video frame feature correlations Judge video and other issues to avoid misjudgments or missed judgments, ensure the independence of the review, and ensure the accuracy of the effect

Active Publication Date: 2020-05-01
GUANGZHOU BAIGUOYUAN INFORMATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, the video review method usually uses the Convolution Neural Network (CNN) model to extract and train the features of each video frame in the Internet video, and uses the trained neural network model to sequentially determine whether there is a violation in a single video frame. Content, and then judge whether the entire Internet video violates the regulations based on the detection results of multiple single video frames.

Method used

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  • Video auditing method and device, auditing server and storage medium
  • Video auditing method and device, auditing server and storage medium
  • Video auditing method and device, auditing server and storage medium

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0032] Figure 1A It is a flow chart of a video review method provided by Embodiment 1 of the present invention. This embodiment can be applied to any situation where Internet videos such as short videos uploaded by users or webcasts are reviewed for violations. A video review method provided in this embodiment can be executed by the video review device provided in the embodiment of the present invention, the device can be realized by means of software and / or hardware, and integrated in the review server that executes the method, The review server may be a background server carrying corresponding video review capabilities.

[0033] Specifically, refer to Figure 1A , the method may include the following steps:

[0034] S110, input each key video frame in the video to be reviewed into the pre-built violation classification model, and obtain the classification score of each key video frame under the corresponding violation subcategory through the binary classification module und...

Embodiment 2

[0047] Figure 2A It is a flow chart of a video review method provided in Embodiment 2 of the present invention, Figure 2B It is a schematic diagram of the principle of the video review process provided by Embodiment 2 of the present invention. This embodiment is optimized on the basis of the foregoing embodiments. Specifically, such as Figure 2A As shown, in this embodiment, a detailed explanation is given for the specific determination process of the violation scores and violation category composition of the video to be reviewed under different violation subcategories.

[0048] optional, such as Figure 2A As shown, the following steps may be included in this embodiment:

[0049] S210, input each key video frame in the video to be reviewed into the pre-built violation classification model, and obtain the classification score of each key video frame under the corresponding violation subcategory through the binary classification module under different violation subcatego...

Embodiment 3

[0063] Figure 3A It is a flow chart of the model training method in the video review method provided by Embodiment 3 of the present invention, Figure 3B It is a schematic diagram of the principle of the model training process in the video review method provided by Embodiment 3 of the present invention. This embodiment is optimized on the basis of the foregoing embodiments. Specifically, such as Figure 3A As shown, in this embodiment, the specific training process of the violation classification model and the violation review model participating in the video review is explained in detail.

[0064] optional, such as Figure 3A As shown, the following steps may be included in this embodiment:

[0065] S310. Extract historical key video frames in the historical video, and determine classification labels of the historical video and historical key frames under different violation subcategories.

[0066] Specifically, in this embodiment, when training the violation classifica...

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PUM

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Abstract

The invention discloses a video auditing method and device, an auditing server and a storage medium. The method comprises the following steps: inputting each key video frame in a to-be-audited video into a violation classification model, and obtaining a classification score of each key video frame under a corresponding violation sub-class through a binary classification module under different violation sub-classes in the violation classification model; for each violation sub-category, fusing the classification score of each key video frame under the violation sub-category to obtain a violationscore of the to-be-audited video under the violation sub-category; and determining violation category composition of the to-be-audited video according to the violation scores of the to-be-audited video under different violation sub-categories and a preset violation threshold. According to the technical scheme provided by the invention, multi-violation category judgment of the to-be-audited videois realized, the problem of misjudgment or missed judgment of violation sub-categories is avoided, the audit independence of the to-be-audited video under different violation sub-categories is ensured, and the comprehensiveness and accuracy of video audit are improved.

Description

technical field [0001] The embodiments of the present invention relate to the field of auditing illegal content in Internet resources, and in particular to a video auditing method, device, auditing server and storage medium. Background technique [0002] With the rapid development of Internet technology, streaming media resources on the Internet have grown explosively, making various short videos or webcast videos and other new user-generated content (User Generated Content, UGC) spread on the Internet more and more abundant. At the same time, a large number of illegal videos involving topics such as terrorism, violence, pornography, or political sensitivity are also produced and quickly spread on the Internet. Therefore, for various types of Internet videos, it is necessary to pre-judge the type of violation to prevent any violation Types of dissemination of Internet video. [0003] At present, video review methods usually use the Convolution Neural Network (CNN) model to ...

Claims

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Application Information

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IPC IPC(8): G06F16/75G06N3/04G06N3/08
CPCG06F16/75G06N3/08G06N3/045G06V20/41G06V20/46G06V10/82G06F18/254
Inventor 孙雪峤石峰刘振强
Owner GUANGZHOU BAIGUOYUAN INFORMATION TECH CO LTD
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