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Optical Flow-Initiated Particle Filter Framework for Human-Tracking and Body-Component Detection

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The principal task in any tracking system is localizing the target motion to minimal bounds, covering target region inside successive video frames. The accuracy of any such system is significantly affected by the initialization parameters. For proper initiation and tracking outcome various methods for target-modeling have been proposed over the years. Our present work focuses on estimation of different body-component positions in a monocular video sequence. We propose a robust particle filtering framework based on optical flow for tracking human in a cluttered scene. The combination of optical flow with the particle filter framework obviates the need for any prior information on target characteristics as the initiation-information is generated online for individual targets. Furthermore, optical flow method provides good initial estimates of target-size and motion characteristics for the prediction stage in particle filter framework. Afterwards, bottom-up search for body-templates has been performed to identify the locations of various body components.
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Keywords: Body-Component Detection; Human Tracking; Optical Flow Motion Extraction; Particle-Filter Tracking

Document Type: Research Article

Affiliations: Department of Computer Science and Engineering, Nitte Meenakshi Institute of Technology, Yelahanka, Bangalore 560064, India

Publication date: November 1, 2017

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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