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Reliable 3D tracking is still a difficult task. Most parametrized 3D deformable models rely on the accurate extraction of image features for updating their parameters, and are prone to failures when the underlying feature distribution assumptions are invalid. Active Shape Models (ASMs), on the other hand, are based on learning, and thus require fewer reliable local image features than parametrized 3D models, but fail easily when they encounter a situation for which they were not trained. Indoi:10.1109/iccv.2007.4409015 dblp:conf/iccv/VoglerLKGM07 fatcat:uaclxgp6kbastihqoytsiz2qwq