Efficient Tracking with AdaBoost and Particle Filter under Complicated Background

Authors:
Yuji Iwahori;Naoki Enda;Shinji Fukui;Haruki Kawanaka;Robert J. Woodham;Yoshinori Adachi
Affiliations:
Faculty of Engineering, Chubu University, Kasugai, Japan 487-8501;Faculty of Engineering, Chubu University, Kasugai, Japan 487-8501;Faculty of Education, Aichi University of Education, Kariya, Japan 448-8542;Faculty of Information Science and Technology, Aichi Prefectural University, Japan 480-1198;Department of Computer Science, University of British Columbia, Vancouver, Canada V6T 1Z4;Faculty of Engineering, Chubu University, Kasugai, Japan 487-8501
Venue:
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
Year:
2008

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Abstract

Particle filter, which is the probability technique, can be used for the robust tracking to the noise and the occlusion. However, when many objects are tracked simultaneously, the real-time tracking becomes difficult as the computational cost increases. While, the AdaBoost has an ability that it has the remarkable efficiency as a statistical technique in pattern recognition. AdaBoost can be used to detect an object region for the efficient tracking with a particle filter. However, it is difficult to detect the moving object under the complicated background by AdaBoost. This paper proposes an improvement of efficiency of particle filter by introducing further distinction features using AdaBoost for the complicated background.