Articulated human body parts detection based on cluster background subtraction and foreground matching

Authors:
Harish Bhaskar;Lyudmila Mihaylova;Simon Maskell
Affiliations:
Department of Electrical and Computer Engineering, Khalifa University, United Arab Emirates;School of Computing and Communications, Lancaster University, UK;Qinetiq, Malvern, UK
Venue:
Neurocomputing
Year:
2013

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Abstract

Detecting people or other articulated objects and localising 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 cluster 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 framework is illustrated over various real-world video sequences.