Compression domain-oriented video content comparison system, optimization method and comparison method

Abstract

The invention belongs to the field of computer vision, particularly relates to a compressed domain-oriented video content comparison system, an optimization method and a comparison method, and aims tosolve the problem of low efficiency of completing video content comparison by using full decoding information. The comparison system comprises: a feature learning module which is used for respectively obtaining feature maps of multiple modes based on multiple pieces of compressed domain information of an input video; a multi-modal compressed domain information fusion module which is used for carrying out information fusion on the multi-modal feature maps output by the feature learning module to obtain a fusion feature vector of the input video; a second module which is configured to obtain the L1 distance of the fusion feature vector of the two input videos; and a classifier which is a binary classification network and is configured to perform binary classification of the comparison result based on the L1 distance output by the second module. According to the invention, high-level semantic information of the video content can be effectively extracted, and high comparison speed and high performance of the video content are ensured.

Description

technical field [0001] The invention belongs to the field of computer vision, and in particular relates to a compression domain-oriented video content comparison system, an optimization method and a comparison method. Background technique [0002] In content-based video understanding systems, a large number of videos usually need to be processed. At present, more than 99% of Internet video traffic is encoded by H264, H265 and other encoding standards. After encoding, the volume of the encoded video is greatly reduced by tens to hundreds of times, but the image information in the video is also converted into indirect information, which needs to be decoded to restore it to the composition of the video. Image frame information. Almost all current video recognition, comparison, retrieval and other algorithms or systems need to decode the video into image frames first, and then process and analyze the image sequence. However, video decoding is very resource-intensive and time-c...

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Problems solved by technology

[0004] In order to solve the above-mentioned problems in the prior art, that is, in order to solve the problem that the efficiency of video content comparison using full video decoding information is not high, the first aspect of the present invention proposes a video content comparison system oriented to the compressed domain, including The first module, the second module, and the classifier connected in sequence;

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