3D face pose estimation based on multi-template AAM

Authors:
Chunsheng Liu;Faliang Chang;Zhenxue Chen
Affiliations:
School of Control Science and Engineering, Shandong University, Ji'nan, China;School of Control Science and Engineering, Shandong University, Ji'nan, China;School of Control Science and Engineering, Shandong University, Ji'nan, China
Venue:
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
Year:
2012

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Abstract

Based on analysis of the pro-existing face pose estimation methods, a new 3D face pose estimation method based on Active Appearance Model(AAM) and T-Structure is proposed. Firstly, a set of multi-view face detection model is established by boosting algorithm to detect multi-view faces. Then, a set of AAM models can be obtained after training different poses faces, and the objective face is matched with the set of AAM models to choose the optimum model to accurate position the key face feature points. Finally, the T structure is built with the two eyes and the mouth, which is used to estimate the face pose. The experiments show that the method can adapt to large rotation angles, and can reach a high accuracy of 3D face pose estimation.