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Viewpoint-independent hand gesture recognition with Kinect

  • School of Computer Science and Technology, Harbin Institute of Technology
  • Princeton University

Research output: Contribution to journalArticlepeer-review

Abstract

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
Pages (from-to)163-172
Number of pages10
JournalSignal, Image and Video Processing
Volume8
Issue number1
DOIs
StatePublished - 2014
Externally publishedYes

Keywords

  • Gesture recognition
  • Kinect
  • Skeleton extraction
  • Viewpoint independent

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