An integrated graph-based face segmentation approach from Kinect videos

In this paper, we present an Integrated Semi-Supervised Graph (IntSSG) approach to automatically segment face from color-depth video. In the first step, IntSSG performs skin color detection and online SIFT matching to initialize some face and non-face pixels. Then, the labels of these pixels are refined by conducting adaptive depth thresholding. Finally, based on a semi-supervised graph framework, IntSSG segments face by propagating the refined labels to other pixels. Experimental results show that IntSSG is able to accurately segment faces in difficult situations such as large pose changes and illumination variations.