S-Log: Skin based Log-Gabor Approach for Face Detection in Video

Visual Surveillance systems have greatly increased in past few years. Several methods have been proposed in order to improve the efficiency of Face Detection but still remains a challenging task due to various illumination, poses and occlusion conditions. In this paper, we propose a novel method for Face Detection where a decision boundary is defined for skin classifier based on training dataset. Log-Gabor filter is used for feature extraction which is superior to Gabor filter as they can represent better frequency properties of the objects present in the video and SVM classifier is used for classifying it as face or non-face. The proposed method is tested on standard and our own collected video sequences, which shows good tolerance and is better than those of existing related algorithms.