Face Feature Locating using Adaptive Active Shape Model

• Main Authors: Cheng-wei Lu, 呂正偉
• Other Authors: Din-chang Tseng
• Format: Others
• Language: en_US
• Online Access: http://ndltd.ncl.edu.tw/handle/73045604258218001753

碩士 === 國立中央大學 === 資訊工程研究所 === 96 === Recently, many face feature locating methods have been proposed. Active shape model has been shown to be a powerful tool to aid the interpretation of images, especially in face alignment. In this study, we propose a face facture location system using adaptive active shape model. The proposed system consists of two parts: (1) training process and (2) testing process. In the training process, we train a mean shape and transform matrix from training images. Then the testing process works by alternating the following steps: (i) Examine a region of image around each point for a better position. (ii) Update the shape parameters to fit the new found positions. In order to locate a better position for each point, we utilize the information of crisscross profiles around each point to decide the best position. We also utilize an adaptive affine transform to get a better reference position during testing process. In the experiments, the proposed approaches are evaluated by several different factors such as profiles, numbers of eigenvalues, and two kinds of affine transform. From the experiment results, we find that the proposed approaches can efficiently locate face feature and have better effect than the classical active shape models.