Real-time multiview recognition of human gestures by distributed image processing

  • Authors:

  • Toshiyuki Kirishima;Yoshitsugu Manabe;Kosuke Sato;Kunihiro Chihara

  • Affiliations:

  • Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma-shi, Nara, Japan;Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma-shi, Nara, Japan;Graduate School of Engineering Science, Osaka University, Toyonaka-shi, Osaka, Japan;Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma-shi, Nara, Japan

  • Venue:
  • Journal on Image and Video Processing - Special issue on fast and robust methods for multiple-view vision
  • Year:
  • 2010

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Abstract

Since a gesture involves a dynamic and complex motion, multiview observation and recognition are desirable. For the better representation of gestures, one needs to know, in the first place, from which views a gesture should be observed. Furthermore, it becomes increasingly important how the recognition results are integrated when larger numbers of camera views are considered. To investigate these problems, we propose a framework under which multiview recognition is carried out, and an integration scheme by which the recognition results are integrated online and in realtime. For performance evaluation, we use the ViHASi (Virtual Human Action Silhouette) public image database as a benchmark and our Japanese sign language (JSL) image database that contains 18 kinds of hand signs. By examining the recognition rates of each gesture for each view, we found gestures that exhibit view dependency and the gestures that do not. Also, we found that the view dependency itself could vary depending on the target gesture sets. By integrating the recognition results of different views, our swarm-based integration provides more robust and better recognition performance than individual fixed-view recognition agents.