Robust lip Localization on Multi-View Faces in Video

In this paper, a fast and robust multi-view lip localization algorithm in video is proposed. We consider lip localization as a binary classification problem, where a classifier is learned to distinguish between the lip and the region surrounding it. The classifier we use here is a histogram-based one which exploits the anthropometrical properties of the human face with the help of face scale normalization. Due to the perceptual uniformity and robustness for lip/skin color variations across different people, we adopt CIELUV color model to represent the color of lip. After classification, we propose a novel projection-cut algorithm by spatial deviation analysis (SDA) to locate the lip, which is effective to deal with the background clutters. Experimental results on teleplay videos demonstrate that the proposed approach is efficient and robust for lip localization.