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

NEUROCOMPUTING

卷:100

Article

Bhaskar, Harish¹  Mihaylova, Lyudmila²  Maskell, Simon³ 

[1] Khalifa Univ, Dept Elect & Comp Engn, Abu Dhabi, U Arab Emirates

[2] Univ Lancaster, Sch Comp & Commun, Lancaster LA1 4YW, England

[3] Qinetiq, Malvern, Worcs, England

关键词: Human target tracking;    Background subtraction;    Optimisation;    Genetic algorithm;    Pictorial structures;   

DOI  :  10.1016/j.neucom.2011.12.039

来源: Elsevier

【 摘 要 】

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. (C) 2012 Elsevier By. All rights reserved.

【 授权许可】

Free