Detecting humans under occlusion using variational mean field method

Authors

Duc Thanh Nguyen, University of WollongongFollow
Philip Ogunbona, University of WollongongFollow
Wanqing Li, University of WollongongFollow

RIS ID

50704

Publication Details

Nguyen, D., Ogunbona, P. & Li, W. (2011). Detecting humans under occlusion using variational mean field method. 18th IEEE International Conference on Image Processing, ICIP 2011 (pp. 2049-2052). USA: IEEE.

Abstract

This paper proposes a human detection method using variational mean field approximation for occlusion reasoning. In the method, parts of human objects are detected individually using template matching. Initial detection hypotheses with spatial layout information are represented in a graphical model and refined through a Bayesian estimation. In this paper, mean field method is employed for such an estimation. The proposed method was evaluated on the popular CAVIAR-INRIA dataset. Experimental results show that the proposed algorithm is able to detect humans in severe occlusion within reasonable processing time.