We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
We present an approach for measuring similarity between visual entities (images or videos) based on matching internal self-similarities. What is correlated across images (or acros...
Matching and registration of shapes is a key issue in Computer Vision, Pattern Recognition, and Medical Image Analysis. This paper presents a shape representation framework based ...
We propose a method for learning using a set of feature representations which retrieve different amounts of information at different costs. The goal is to create a more efficient ...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
A novel algorithm for robustly segmenting changes between different images of a scene is presented. This computationally efficient algorithm is based on a non-linear comparison of...