Lips detection using self-organizing map and reinforcement learning

• Main Authors: Jiun-Hung Chen, 陳俊宏
• Other Authors: Cheng-Yuan Liou
• Format: Others
• Language: en_US
• Published: 1999
• Online Access: http://ndltd.ncl.edu.tw/handle/28663252445109968468

碩士 === 國立臺灣大學 === 資訊工程學研究所 === 87 === Traditional lips detection methods consist of a binary classifiers which can classify lips and nonlips followed by some search algorithms. The search algorithms may depend on some face anatomatical information or heuristics. They do not learn any structural inforamiton while searching. A new lips detection approach is proposed. It solves classificaition and search at the same time based on structural infomation in faces. There are three main parts in this proposed approach. First, face detection is based on color and shape information and autocorrelation functions and golbal maximum difference are used as features for face image. Second, features are then clustered by self organizing map to form states. Third, by modeling the lips detection as a Markovian decision process, reinforcment learning is applied to find a optimal policy. The capability of this approach is demostrated by experimental results.