We derive a probabilistic framework for robust, realtime, visual tracking of multiple previously unseen objects from a moving camera. This framework models the discrete depth orde...
This paper presents a geometric approach to recognizing smooth objects from their outlines. We define a signature function that associates feature vectors with objects and baseline...
Svetlana Lazebnik, Amit Sethi, Cordelia Schmid, Da...
Acquiring transparent, refractive objects is challenging as these kinds of objects can only be observed by analyzing the distortion of reference background patterns. We present a ...
Gordon Wetzstein, David Roodnick, Wolfgang Heidric...
letons to Bone Graphs: Medial Abstraction for Object Recognition Diego Macrini University of Toronto Kaleem Siddiqi McGill University Sven Dickinson University of Toronto Medial d...
This paper presents a method that uses the level sets of volumes to reconstruct the shapes of 3D objects from range data. The strategy is to formulate 3D reconstruction as a stati...