Recognition of three dimensional (3D) objects in noisy and cluttered scenes is a challenging problem in 3D computer vision. One approach that has been successful in past research i...
Andrea Frome, Daniel Huber, Ravi Kolluri, Thomas B...
In this paper, we present an efficient algorithm which discovers rare episodes with a combination of bottomup and top-down scanning schema. The information sharing between bottom-...
We present the Higher Order Proxy Neighborhoods (HOPS) approach to modeling higher order neighborhoods in Markov Random Fields (MRFs). HOPS incorporates more context information i...
We present a simple and efficient dense matching method based on region growing techniques, which can be applied to a wide range of globally textured images like many outdoor scen...
Abstract. This paper introduces an efficient way of representing textures using connected regions which are formed by coherent multi-scale over-segmentations. We show that the rece...