Wavelet-based skin segmentation for detecting occluded arms in human body pose modelling system

The task of correctly tracking the body parts is one of the crucial problems in the human body pose modelling. Various factors need to be investigated as the variety of body poses is unlimited and the visual appearance varies according to the environment. The human body can be composed into several parts such as the head, torso, arms and legs. The arms can be considered as the most challenging body part to be tracked since it tends to move fast and usually occluded within other body parts. This paper addresses the problem of extracting the arms which are occluded in the torso part. A wavelet-based skin segmentation method is applied to detect the skin region. The segmentation procedure is performed using six different colour spaces namely the RGB, rgb, HSI, TSL, SCT and CIELAB. The segmentation performances are evaluated on colour component basis. The aim of this paper is to determine the best colour components that are suitable for this segmentation procedure.