In this paper we present a system that combines the benefits of 3D deformable models and level set methods for medical volume segmentation. Our 3D deformable model is a very comp...
Derek R. Magee, Andrew J. Bulpitt, Elizabeth Berry
We present a closed form solution to the problem of segmenting multiple 2-D motion models of the same type directly from the partial derivatives of an image sequence. We introduce...
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. A new, exemplar-based, probabilistic paradigm for visual tracking is presented. Probabilistic mechanisms are attractive because they handle fusion of information, especia...
We describe and compare three probabilistic ways to perform Content Based Image Retrieval (CBIR) in compressed domain using images in JPEG2000 format. Our main focus are arbitrary ...