Combining Facial Features and Relevance Vector Machine for Multi-pose Face Detection
Yin Jun-xun · Science Technology and Engineering · 2010
Multi-pose face detection has been one of difficult and hot issues in face detection research.For this practical application problem urgently need to be solved, a multipose face detection algorithm based on facial features and relevance vector machine algorithm is introduced.Making full use of skin color information firstly, the most background regions can be quickly excluded.After detecting eyes and mouth in the skin color regions, according to face orientation decided by the geometric features of the eyes and mouth region, the approximate frontal face candidates are segmented.At last, the face candidates are classified by relevance vector machine algorithm, which its classification performance is better than support vector machine.The experimental results demonstrate that the algorithm can further improve the multi-pose face detection accuracy and is highly robust to lighting condition, facial expression and occlusion.