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

Research output: Contribution to Journal/MagazineJournal articlepeer-review

<mark>Journal publication date</mark>16/01/2013
Issue number1
Number of pages16
Pages (from-to)58-73
Publication StatusPublished
Early online date11/05/12
<mark>Original language</mark>English


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.