Abstract
We address the problem of automatically placing landmarks across an image sequence to define correspondences between frames. The marked up sequence is then used to build a statistical model of the appearance of the object within the sequence. We locate the most salient object features from within the first frame and attempt to track them throughout the sequence. Salient features are those which have a low probability of being mis-classified as any other feature, and are therefore more likely to be robustly tracked throughout the sequence. The method automatically builds statistical models of the objects shape and the salient features appearance as the sequence is tracked. These models are used in subsequent frames to further improve the probability of finding accurate matches. Results are shown for several face image sequences. The quality of the model is comparable with that generated from hand labelled images.
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