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Active appearance models (AAMs) typically only use 50-100 mesh vertices because they are usually constructed from a set of training images with the vertices hand-labeled on them. In this paper, we propose an algorithm to increase the density of an AAM. Our algorithm operates by iteratively building the AAM, refitting the AAM to the training data, and refining the AAM.We compare our algorithm with...
The quantitative evaluation of optical flow algorithms by Barron et al. led to significant advances in the performance of optical flow methods. The challenges for optical flow today go beyond the datasets and evaluation methods proposed in that paper and center on problems associated with nonrigid motion, real sensor noise, complex natural scenes, and motion discontinuities. Our goal is to establish...
Active appearance models (AAMs) are generative parametric models commonly used to track faces in video sequences. A limitation of AAMs is they are not robust to occlusion. A recent extension reformulated the search as an iteratively re-weighted least-squares problem. In this paper we focus on the choice of error function for use in a robust AAM search. We evaluate eight error functions using two performance...
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