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深度图像中基于部位位置及尺寸的人体识别方法 被引量：3

Human Body Recognition from Depth Image Based on Part Size and Position
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摘要 人体姿态估计方法中,在初始化或者跟踪失败的情况下,需要提供姿态初始值。我们将姿态估计看作对人体每个像素的分类问题,设计了一种表征人体部位尺寸及位置的特征。通过识别当前帧人体像素所属部位,可计算人体姿态。我们对分类器性能进行了测试,分类器对人体像素的识别率达到91%,对分辨率为160*120的深度图像,Intel单核1.6GHZ的处理器上的处理速度为4ms/fps。本文分析了该特征的局限性及出现问题的原因。 Human action recognition acts as an important role in human machine interaction.This paper proposes a human body recognition method from depth image based on part size and position features.Random forest classifiers are trained with different parameters.Experimental results demonstrate the feasibility of proposed approach.Recognition accuracy is about 91% and the computation time is about 0.96 us per pixel.
作者 赵文闯 程俊
机构地区 中国科学院深圳先进技术研究院
出处 《集成技术》 2012年第3期10-14,共5页 Journal of Integration Technology
基金 中国科学院院地合作项目(ZNGZ-2011-012) 深圳市深港创新圈项目(JSE201007200037A)资助
关键词 人体姿态估计 随机森林 human body recognition random forest
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
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参考文献13

  • 1Siddiqui M,Medioni G.Human pose estimation from a single view point, real-time range sensor. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) . 2010
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同被引文献38

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集成技术
2012年 第3期

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