A Real-Time Applicable Dynamic Hand Gesture Recognition Framework

The authors present a system for efficient dynamic hand gesture recognition based on a single time-of-flight sensor. As opposed to other approaches, the authors simply rely on depth data to interpret user movement with the hand in mid-air. The authors set up a large database to train multilayer perceptrons (MLPs) which are subsequently used for classification of static hand poses that define the targeted dynamic gestures. In order to remain robust against noise and to balance the low sensor resolution, PCA is used for data cropping and highly descriptive features, obtainable in real-time, are presented. This simple yet efficient definition of a dynamic hand gesture shows how strong results are achievable in an automotive environment allowing for interesting and sophisticated applications to be realized.


  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 2358-2363
  • Monograph Title: 18th International IEEE Conference on Intelligent Transportation Systems (ITSC 2015)

Subject/Index Terms

Filing Info

  • Accession Number: 01601000
  • Record Type: Publication
  • ISBN: 9781467365956
  • Files: TRIS
  • Created Date: May 2 2016 3:21PM