An ideal shape model should be both invariant to global transformations and robust to local distortions. In this paper we present a new shape modeling framework that achieves both...
We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
Abstract. We present an alignment framework for object detection using a hierarchy of 3D polygonal models. One difficulty with alignment methods is that the high-dimensional transf...
Reliable segmentation of the left ventricle is a long sought objective in medical imaging for automatic retrieval of anatomical and pathological measurements and detection of malf...
We propose a mathematical framework for a unification of the distributional theory of meaning in terms of vector space models, and a compositional theory for grammatical types, fo...