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A 3D face shape derived from 2D images may be useful in many applications, such as face recognition, face synthesis and human computer interaction. To do this, we develop a fast 3D Active Appearance Model (3D-AAM) method using depth estimation. The training images include specific 3D face poses which are extremely different from one another. The landmark's depth information of landmarks is estimated...
Face tracking and recognition are not easy because the face is a non-rigid object. The main reasons for the failure to track and recognize faces are changes of pose and environmental illumination. In this paper, we propose a preprocessing method that compensates for illumination variations and a nonlinear manifold framework to deal with pose changes in the face. For video-based face recognition system,...
Scene change detection is the first step for automatic indexing of video data. In particular, it is desirable to detect scene changes on compressed data because this requires less processing overhead and storage to hold the results. Some approaches are proposed to detect scene changes on compressed data by computing the variances of DCT coefficients. However, these approaches do not consider the content...
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