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[17] Yasuda T, Matsumura Y, Ohkura K , Extended pso with partial randomization for large scale multimodal problems, World Automation Congress , 2010, 1–6.","bibtexUrl_cn":"//www.sanmikaiseki.com/jns/CN/article/getTxtFile.do?fileType=BibTeX&id=537","abstractUrl_en":"https://jns.nju.edu.cn/EN/Y2015/V51/I2/297","qi":"2","id":537,"nian":2015,"bianHao":"201412011","zuoZheEn_L":"Zhou Wenmeng1,Yang Yipin1, Zhou Yu1, Yu Yao1, Jin Suwen2, Du Sidan1*","juanUrl_en":"https://jns.nju.edu.cn/EN/Y2015","shouCiFaBuRiQi":"2015-03-31","qiShiYe":"297","qiUrl_cn":"//www.sanmikaiseki.com/jns/CN/Y2015/V51/I2","lanMu_cn":"","pdfSize":"1550955","zuoZhe_CN":"周文猛1，杨一品1，周余1，于耀1，金苏文2，都思丹1*","risUrl_cn":"//www.sanmikaiseki.com/jns/CN/article/getTxtFile.do?fileType=Ris&id=537","title_cn":"基于Kinect的无标记手部姿态估计系统","jieShuYe":"","endNoteUrl_cn":"//www.sanmikaiseki.com/jns/CN/article/getTxtFile.do?fileType=EndNote&id=537","zhaiyao_en":"As computer technology is developing, more and more human-computer interaction methods come out, such as voice control, hand control and human body control. In this paper, we present a novel approach to recover and track the 3D position, orientation and the full articulated information of a human hand from a video sequence obtained by a Kinect sensor. By using Particle Swarm Optimization (PSO) variant to minimize the cost function which quantifies the discrepancy between projected model and the ground truth observations , we can get the motion parameters of the hand observed by the Kinect sensor. In order to accelerate PSO, continuity over frame sequence is exploited by setting the initial states of particles of current frame to the optimized ones of the previous frame. Moreover, GPU acceleration is adopted due to the inherent parallelization and optimized for images processing of hands. The overall system does not need any markers or special environment and c an be performed in 20Hz","bibtexUrl_en":"https://jns.nju.edu.cn/EN/article/getTxtFile.do?fileType=BibTeX&id=537","abstractUrl_cn":"https://jns.nju.edu.cn/CN/Y2015/V51/I2/297","zuoZheCn_L":"周文猛1，杨一品1，周余1，于耀1，金苏文2，都思丹1*","juanUrl_cn":"https://jns.nju.edu.cn/CN/Y2015","lanMu_en":"","qiUrl_en":"https://jns.nju.edu.cn/EN/Y2015/V51/I2","zuoZhe_EN":"Zhou Wenmeng1,Yang Yipin1, Zhou Yu1, Yu Yao1, Jin Suwen2, Du Sidan1*","risUrl_en":"https://jns.nju.edu.cn/EN/article/getTxtFile.do?fileType=Ris&id=537","title_en":"Markerless hand pose estimation system using Kinect","hasPdf":"true"},"authorNotes_cn":["(1.南京大学电子科学与工程学院,南京,210023;2.上海协同科技,上海,200063)"]}">

基于Kinect的无标记手部姿态估计系统

周文猛1，杨一品1，周余1，于耀1，金苏文2，都思丹1*

南京大学学报(自然科学版)››2015, Vol. 51››Issue (2): 297.

PDF(1550955 KB)

PDF(1550955 KB)

南京大学学报(自然科学版) ›› 2015, Vol. 51 ›› Issue (2) : 297.

基于Kinect的无标记手部姿态估计系统

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Markerless hand pose estimation system using Kinect

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