Articulated Human Body Parts Detection Based on Cluster Background Subtraction and Foreground Matching

Bhaskar, Harish and Mihaylova, Lyudmila and Maskell, S. (2013) Articulated Human Body Parts Detection Based on Cluster Background Subtraction and Foreground Matching. Neurocomputing, 100 (1). pp. 58-73. ISSN 0925-2312

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Abstract

Detecting people or other articulated objects and localizing their body parts is a challenging computer vision problem as their movement is unpredictable under circumstances of partial and full occlusions. In this paper, a framework for human body parts tracking in video sequences using a self-adaptive clus- ter background subtraction (CBS) scheme is proposed based on a Gaussian mixture model (GMM) and foreground matching with rectangular pictorial structures. The efficiency of the designed human body parts tracking frame- work is illustrated over various real-world video sequences.

Item Type: Journal Article
Journal or Publication Title: Neurocomputing
Uncontrolled Keywords: /dk/atira/pure/subjectarea/asjc/1700/1706
Subjects:
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 52306
Deposited By: ep_importer_pure
Deposited On: 20 Jan 2012 11:10
Refereed?: Yes
Published?: Published
Last Modified: 23 Feb 2020 01:42
URI: https://eprints.lancs.ac.uk/id/eprint/52306

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