Abstract
Active or deformable models have emerged as a popular modeling paradigm in computer vision. These models have the flexibility to adapt themselves to the image data, o ering the potential for both generic object recognition and non-rigid object tracking. Because these active models are underconstrained, however, deformable shape recovery often requires manual segmentation or good model initialization, while active contour trackers have been able to track only an object's translation in the image. In this paper, we report our current progress in using a part-based aspect graph representation of an object [14] to provide the missing constraints on data-driven deformable model recovery and tracking processes.