Video fingerprint detection and video sequence matching method and system based on visual features

Abstract

The invention proposes a video fingerprint detection method based on visual features, specifically: segment the video sequence according to the inter-frame correlation, extract key frames in the segments; extract video features in each key frame; use pixel feature dictionary Classify the pixels; divide each key frame into multiple different numbers of blocks, count the occurrence times of each element of the pixel feature dictionary in each sub-block according to the classification results of the pixels, and obtain the feature vector of the sub-block; The eigenvectors of all sub-blocks are concatenated to obtain the high-dimensional video fingerprints of the key frames; the dimensionality of each high-dimensional video fingerprint is reduced; the low-dimensional video fingerprints of the key frames of each video segment are connected in chronological order into a key frame video fingerprint string. The present invention also provides a video matching method based on the above-mentioned fingerprint detection method. The invention effectively describes the key information of the video content, greatly reduces the complexity of the algorithm and effectively improves the detection efficiency without affecting the matching rate.

Description

technical field [0001] The invention belongs to the field of video analysis, in particular to a video fingerprint detection and video sequence matching method based on visual features. Background technique [0002] With the rapid development of computer technology and network, the number of online videos is increasing rapidly. At the same time, with the development of video processing technology, video editing has become easier. For video content, content deletion, resolution change, content occlusion, content replacement, and noise increase all increase the detection of related video content. difficulty. How to effectively establish video fingerprints so as to be able to detect relevant video content under the premise of certain video editing has become an increasingly urgent demand. [0003] At present, the main video sequence matching methods can be divided into two categories. The first method is a global brightness analysis method. This method analyzes the brightnes...

AI Technical Summary

Problems solved by technology

This kind of method based on motion trajectory analysis can track key objects, so it is more robust than the method based on global brightness, but its computational complexity is very high, and it needs to detect and track key objects, so it has high efficiency. certain limitations

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