Video Action Matching Algorithm Based on Dynamic Compression and Constraint Search
This study conducted a research based on the action alignment method of computer vision,and proposed a video action alignment method based on human pose recognition algorithm,action sequence data compression,and constraint search path dynamic time warping(DTW)algorithm.This comparison method first utilized a human posture recognition network to obtain two-dimensional coordinate data of key joint points in human motion and converted it into joint angle features.Secondly,an optimized dual threshold dynamic data compression method was used to obtain short sequences of joint features in action videos.Finally,the optimization algorithm of dynamic time warping was used to calculate the similarity of the two compressed short video sequences so as to realize the comparison of human motion joints.The ex-perimental results confirmed the efficiency of the optimization algorithm,reducing the matching time from 16.353 seconds to just 0.079 0 seconds for Baduanjin video data,highlighting a significant advantage in terms of time savings in computation.
human pose recognitionaction comparisondynamic time regulationconstrained searchdy-namic compressiontime series
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