Head gesture recognition based on bayesian network

Authors:
Peng Lu;Xiangsheng Huang;Xinshan Zhu;Yangsheng Wang
Affiliations:
Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China
Venue:
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
Year:
2005

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Abstract

Head gestures such as nodding and shaking are often used as one of human body languages for communication with each other, and their recognition plays an important role in the development of Human-Computer Interaction (HCI). As head gesture is the continuous motion on the sequential time series, the key problems of recognition are to track multi-view head and understand the head pose transformation. This paper presents a Bayesian network (BN) based framework, into which multi-view model (MVM) and the head gesture statistic inference model are integrated for recognizing. Finally the decision of head gesture is made by comparing the maximum posterior, the output of BN, with some threshold. Additionally, in order to enhance the robustness of our system, we add the color information into BN in a new way. The experimental results illustrate that the proposed algorithm is effective.