Using Aspect Graphs to Control the Recovery and Tracking of Deformable Models
AbstractActive 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, offering 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  to provide the missing constraints on data-driven deformable model recovery and tracking processes. Appears in International Journal of Pattern Recognition and Artificial Intelligence, Vol. 11, No. 1, February, 1997, pp 115--142. (special issue containing selected papers from the Workshop on Spatial Computing: Representation, Interpretation and Applications, Curtin University of ..