Conference Paper2015

Feature fusion for robust object tracking

MA Islam, M Rasheduzzaman, MM Lutfe Elahi, Bruce Poon, M Ashraful Amin, Hong Yan

2015 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

IEEE, pp. 138–145

DOI: 10.1109/icwapr.2015.7295940URL

Abstract

This paper addresses the problem of long term object tracking in a video stream. Our main objective is to determine object's location in every frame that follows. We propose a tracking framework that explicitly decomposes the long term tracking task into tracking, detection and fusion. These three sub-systems are connected in one functional system, which addresses the problem of long term object tracking. The tracker follows the object from frame to frame. The detector observes all appearances and corrects the tracker if necessary. Detection model is integrated to enhance the tracking performance. Output from Lucas-Kanade Tracker and radial sub-window based detector are combined in the fusion part. We use benchmark sequences of MIL datasets which are widely used by other tracking algorithms. We employ the standard center location error and precision for assessing performance of our proposed method. Our tracking system outperforms other state-of-the-art tracking systems in four sequences considering the center location error.

Keywords

  • feature fusion
  • long-term object tracking
  • video streams

CCDS Authors

Prof. M Ashraful Amin, PhD
M Ashraful Amin, PhD

Prof. M Ashraful Amin, PhD

  • Founder Director, CCDS
  • Director, AI/ML, HCI & DS Wings

Professor

+1 more affiliation

Department of Information Sciences and Technology

George Mason University, USA

Published at

ACL, CHI, UbiComp, ECAI, WACV, PAKDD, IJCNN, ICPR, ICIP, HCII, CLEF, BLP, Scientific Reports, JMIR, IEEE Access, Smart Agricultural Technology, Frontiers in Computational Neuroscience, Diabetes Research and Clinical Practice, PLOS ONE

Research Interests

Machine Learning, Cognitive & Vision Science, Cybernetics, Surveillance & Security, ICT in Education, Health, & Agriculture, Human-Computer Interaction, Internet of Things, Robotics

References

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