Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
We propose a new methodology for fusing temporally changing multisensor raster and vector data by developing a spatially and temporally varying uncertainty model of acquired and t...
We present a real-time method for detecting deformable surfaces, with no need whatsoever for a priori pose knowledge. Our method starts from a set of wide baseline point matches be...
Abstract. Classification of structured data (i.e., data that are represented as graphs) is a topic of interest in the machine learning community. This paper presents a different,...
Several application and technology trends indicate that it might be both pro table and feasible to move computation closer to the data that it processes. In this paper, we evaluat...