Viewpoint-independent hand gesture recognition with Kinect

被引:11
|
作者
Jiang, Feng [1 ]
Wu, Shen [1 ]
Yang, Gao [1 ]
Zhao, Debin [1 ]
Kung, S. Y. [2 ]
机构
[1] Harbin Inst Technol, Sch Comp Sci, Harbin 150001, Peoples R China
[2] Princeton Univ, Sch Elect Engn, Princeton, NJ 08544 USA
基金
中国国家自然科学基金;
关键词
Gesture recognition; Viewpoint independent; Kinect; Skeleton extraction; SKELETON;
D O I
10.1007/s11760-014-0668-x
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The advent and popularity of Kinect provide new choice and opportunity for hand gesture recognition research. Aiming at the effective, accurate and freely used hand gesture recognition with Kinect, this paper presents a viewpoint-independent hand gesture recognition method. Firstly, based on the rules about gesturers posture under optimal viewpoint, the gesturers point clouds are built and transformed to the optimal viewpoint with the exploration of the joint information. Then Laplacian-based contraction is applied to extract representative skeletons from the transformed point clouds. A novel partition-based algorithm is further proposed to recognize the gestures. The promising experiment results show that the proposed method performs satisfyingly on scale and rotation variant in HGR with robustness and high accuracy.
引用
收藏
页码:S163 / S172
页数:10
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