We present a novel representation of maps between pairs of shapes that allows for efficient inference and manipulation. Key to our approach is a generalization of the notion of m...
We describe a method for learning steerable deformable part models. Our models exploit the fact that part templates can be written as linear filter banks. We demonstrate that one...
We describe a set of image measurements which are invariant to the camera internals but are location variant. We show that using these measurements it is possible to calculate the...
Michael Werman, MaoLin Qiu, Subhashis Banerjee, Su...
We describe the use of a translation memory in the context of a reconstruction of a landmark application of machine translation, the Canadian English to French weather report trans...
We describe techniques for performing mobile robot localization using occupancy grids that allow subpixel localization and uncertainty estimation in the pixelized pose space. The ...