Survey on 3D Hand Gesture Recognition

Abstract
Three-dimensional hand gesture recognition has attracted increasing research interests in computer vision, pattern recognition, and human-computer interaction. The emerging depth sensors greatly inspired various hand gesture recognition approaches and applications, which were severely limited in the 2D domain with conventional cameras. This paper presents a survey of some recent works on hand gesture recognition using 3D depth sensors. We first review the commercial depth sensors and public data sets that are widely used in this field. Then, we review the state-of-the-art research for 3D hand gesture recognition in four aspects: 1) 3D hand modeling; 2) static hand gesture recognition; 3) hand trajectory gesture recognition; and 4) continuous hand gesture recognition. While the emphasis is on 3D hand gesture recognition approaches, the related applications and typical systems are also briefly summarized for practitioners.
Funding Information
  • National Natural Science Foundation of China (61305033, 61273256)
  • Fundamental Research Funds through the Central Universities (ZYGX2013J088, ZYGX2014Z009)
  • Scientific Research Foundation for the Returned Overseas Chinese Scholars, state Education Ministry

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