Recent methods and databases in vision-based hand gesture recognition: A review

Pramod Kumar Pisharady, Martin Saerbeck

Research output: Contribution to journalArticlepeer-review

133 Scopus citations

Abstract

Successful efforts in hand gesture recognition research within the last two decades paved the path for natural human-computer interaction systems. Unresolved challenges such as reliable identification of gesturing phase, sensitivity to size, shape, and speed variations, and issues due to occlusion keep hand gesture recognition research still very active. We provide a review of vision-based hand gesture recognition algorithms reported in the last 16 years. The methods using RGB and RGB-D cameras are reviewed with quantitative and qualitative comparisons of algorithms. Quantitative comparison of algorithms is done using a set of 13 measures chosen from different attributes of the algorithm and the experimental methodology adopted in algorithm evaluation. We point out the need for considering these measures together with the recognition accuracy of the algorithm to predict its success in real-world applications. The paper also reviews 26 publicly available hand gesture databases and provides the web-links for their download.

Original languageEnglish (US)
Pages (from-to)152-165
Number of pages14
JournalComputer Vision and Image Understanding
Volume141
DOIs
StatePublished - Dec 1 2015
Externally publishedYes

Keywords

  • Gesture database
  • Gesture recognition
  • Hand gesture dataset
  • Hand pose estimation
  • Posture recognition
  • Sign language recognition
  • Survey

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