Viewpoint-independent hand gesture recognition with Kinect

Feng Jiang, Shen Wu, Gao Yang, Debin Zhao, S. Y. Kung

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)163-172
Number of pages10
JournalSignal, Image and Video Processing
Issue number1
StatePublished - 2014

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering


  • Gesture recognition
  • Kinect
  • Skeleton extraction
  • Viewpoint independent


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