基于时空纹理特征的3D人体行为分析系统
首发时间:2014-10-17
摘要:当前面向深度视频信息的三维人体行为视频被广泛应用到体感交互和行为分析领域中。为了在现实场景中更好的分析人体行为,提出了一种基于时空纹理特征的人体行为视频识别方法和系统。首先利用Kinect等体感设备采集人体行为视频,并对行为视频进行预处理,然后对视频进行三维时空纹理特征提取,生成人体行为特征信息模型;进而完成分类识别,最后在行为分析系统上实现模拟个性化控制。相比于过去的识别方法,文中方法简化了视频人体行为识别的复杂度,降低了行为特征数据量,并取得了较好的系统分析效果。
关键词: 人体行为识别 时空纹理特征 深度视频 行为分析系统
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3D Human Behavior Analysis System based on Spatiotemporal Texture Features
Abstract:Currently 3D human behavior videos containing depth information have been widely applied to areas of body sensing interaction and behavior analysis. In order to better analyze human behavior in real-life scenarios, a human behavior video recognition method and system is proposed based on temporal texture features. First of all, Kinect and other somatosensory equipment are employed to capture human behavior videos, which are then preprocessed. Afterwards, the three-dimensional temporal texture features are extracted to generate a human behavior feature information model; then classification and recognition is accomplished and analog personality control is realized on the behavior analysis system. Compared to previous recognition methods, the proposed method has simplified the complexity of human behavior recognition in the videos, reduced the data size of behavioral features, and achieved good system analysis results.
Keywords: Human behavior recognition Spatiotemporal texture features Depth videos Behavior analysis system
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No.4612773100628014****
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