三维模拟序列图与视频动作识别技术相结合在评估和纠正舞者舞蹈动作中的作用

Hua Wei, Vinh Chau
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引用次数: 0

摘要

本文将舞蹈三维空间模拟序列图与视频动作识别技术相结合,对采集到的舞蹈视频图像进行滤波、去噪、去灰、去背景等处理,分析序列图中人物的动作特征,利用支持向量机学习和训练三维空间模型,对人物的舞蹈动作进行分类和识别,提取人体各部位的三维-SIFT和光流特征。形成三维空间模拟序列图,对提取的特征进行还原和归一化处理,得到各种人物的特征向量,并将其输入分类器,实现对舞蹈动作的识别。结果表明,三维-SIFT与光流的结合可以实现人体静态信息的动态变化,SIFT特征的光照不变性可以弥补光流特征的光照敏感性,光流特征可以解决SIFT特征关键点确定的不稳定性问题。
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The Role of the Combination of 3D Simulation Sequence Diagram and Video Motion Recognition Technology in Evaluating and Correcting Dancers' Dance Moves
This paper combines the dance 3D space simulation sequence diagram with video motion recognition technology, filters, denoises, grays and background removal the collected dance video images, analyzes the motion characteristics of people in the sequence diagram, uses support vector machine to learn and train 3D space models, classifies and recognizes people's dance movements, and extracts 3D-SIFT and optical flow characteristics of various areas of human body. Form a three-dimensional space simulation sequence diagram, reduce and normalize the extracted features, get the feature vectors of various characters, and input them into the classifier to realize the recognition of dance movements. The results show that the combination of 3D-SIFT and optical flow can realize the dynamic change of human static information, the illumination invariance of SIFT features can make up for the illumination sensitivity of optical flow features, and the optical flow features can solve the instability problem of determining the key points of SIFT features.
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来源期刊
CiteScore
1.40
自引率
16.70%
发文量
23
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