Motion divergence fields for dynamic hand gesture recognition

Xiaohui Shen*, Gang Hua, Lance Williams, Ying Wu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Although it is in general difficult to track articulated hand motion, exemplar-based approaches provide a robust solution for hand gesture recognition. Presumably, a rich set of dynamic hand gestures are needed for a meaningful recognition system. How to build the visual representation for the motion patterns is the key for scalable recognition. We propose a novel representation based on the divergence map of the gestural motion field, which transforms motion patterns into spatial patterns. Given the motion divergence maps, we leverage modern image feature detectors to extract salient spatial patterns, such as Maximum Stable Extremal Regions (MSER). A local descriptor is extracted from each region to capture the local motion pattern. The descriptors from gesture exemplars are subsequently indexed using a pre-trained vocabulary tree. New gestures are then matched efficiently with the database gestures with a TF-IDF scheme. Our extensive experiments on a large hand gesture database with 10 categories and 1050 video samples validate the efficacy of the extracted motion patterns for gesture recognition. The proposed approach achieves an overall recognition rate of 97.62%, while the average recognition time is only 34.53 ms.

Original languageEnglish (US)
Title of host publication2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011
Pages492-499
Number of pages8
DOIs
StatePublished - Jun 17 2011
Event2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011 - Santa Barbara, CA, United States
Duration: Mar 21 2011Mar 25 2011

Publication series

Name2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011

Other

Other2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011
CountryUnited States
CitySanta Barbara, CA
Period3/21/113/25/11

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition

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