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This paper presents a novel method to estimate the pose of human faces from insufficient video data. We represent each pose of a person's face as a connected low-dimensional appearance manifolds which are approximated by affine plane. To construct affine planes, we first sample exemplars from video data and cluster exemplars into each pose. From exemplars, the affine plane is constructed using PCA...
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,...
Face pose-based robot control plays an important role in natural human-robot interaction. In this paper, we propose a robust face pose estimation method based on manifold learning to control the wheeled robot. We represent each pose of a person's face as a connected low-dimensional appearance manifolds which are approximated by affine plane. Pose recognition task is to find sub-pose by computing the...
For efficient viewing of the comics, it is desirable for the user to non-linearly control the viewing order of panels in comics and manipulate size and colors of objects in the specified panel. In this paper, we present human robot interaction techniques using face pose, facial expression and hand gesture for viewing comics on the robot. The user's face pose is used to control viewing order of panels...
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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