3D Motion Recognition based on Ensemble Learning

Authors:
HongLi Zhu;PengYing Du;Jian Xiang
Affiliations:
Zhe Jiang University;Zhe Jiang University;Zhe Jiang University
Venue:
WIAMIS '07 Proceedings of the Eight International Workshop on Image Analysis for Multimedia Interactive Services
Year:
2007

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Abstract

In this paper, a novel method is presented for 3D motion recognition based on Motion Capture Database. We use 3D features and their keyspaces of each human joint to represent human motion. After features extraction, Ensemble HMM learners are used to train data. Then each action class is learned with one HMM and bagging algorithm is used to ensemble all learners. Since ensemble learning can effectively enhance supervised learners, ensembles of weak HMM learners are built. It is obvious thatthe proposed methods are effective by experimental results.