We propose an approach for detecting objects in large-scale range datasets that combines bottom-up and top-down processes. In the bottom-up stage, fast-to-compute local descriptors...
Alexander Patterson, Philippos Mordohai, Kostas Da...
Local feature approaches to vision geometry and object recognition are based on selecting and matching sparse sets of visually salient image points, known as `keypoints' or `p...
This paper presents a sparse representation of 2D planar shape through the composition of warping functions, termed formlets, localized in scale and space. Each formlet subjects t...
We present a new reliable dense disparity estimation algorithm which employs Gaussian scale-space with anisotropic disparity-field diffusion. This algorithm estimates edge-preserv...
We show that a resealed constrainedness parameter provides the basis for accurate numerical models of search cost for both backtracking and local search algorithms. In the past, t...
Ian P. Gent, Ewan MacIntyre, Patrick Prosser, Toby...