3D Head pose-normalization using 2D and 3D interaction

Pose-variation factors present a significant problem in 2D face recognition. To solve this problem, there are various approaches for a 3D face acquisition system which was able to generate multi-view images. However, this created another pose estimation problem in terms of normalizing the 3D face data. This paper presents a 3D head pose-normalization method using 2D and 3D interaction. The proposed method uses 2D information with the AAM(active appearance model) and 3D information with a 3D normal vector. In order to verify the performance of the proposed method, we designed an experiment using DP(dynamic programming). Experimental results showed that the proposed method is robust against pose variation.