A REVIEW ON: MULTIPLE FACE DETECTION AND TRACKING USING SKIN TONE SEGMENTATION TECHNIQUE

Abstract

Recent years have witnessed renewed interest in developing skin segmentation approaches. Skin feature segmentation has been widely employed in different aspects of computer vision applications including face detection and tracking systems. This is mostly due to the attractive characteristics of skin color and its effectiveness to object segmentation. On the contrary, there are certain challenges in using human skin color as a feature to segment dynamic face features, due to various illumination conditions, complicated environment, and computation time or real-time method. These challenges have led to the insufficiency of many of the skin color segmentation approaches. Therefore, to produce simple, effective, and cost efficient skin segmentation, a localized approach for multiple face detection and tracking in input video are proposed which is based on skin tone segmentation algorithm and dynamic facial features (eyes, nose, and mouth) extraction method which increase accuracy of detection and tracking multiple faces in video. In this proposed work, segmentation of skin regions from a video frames is done by using RGB color model which help to remove non skin like pixel from a video frames. Each segmented skin regions are tested to know whether region contain human face or not, by extracting facial features. Once the face is detected then they are tracked in video. The experimental results showed that the proposed scheme achieved good performance in terms of accuracy and computation time.