One of the principal bottlenecks in applying learning techniques to classification problems is the large amount of labeled training data required. Especially for images and video, ...
Ajay J. Joshi, Fatih Porikli, Nikolaos Papanikolop...
We present a novel variant of the RANSAC algorithm
that is much more efficient, in particular when dealing with
problems with low inlier ratios. Our algorithm assumes
that there...
We consider learning models for object recognition from examples. Our method is motivated by systems that use the Hausdorff distance as a shape comparison measure. Typically an ob...
Depth from triangulation has traditionally been treated in a number of separate threads in the computer vision literature, with methods like stereo, laser scanning, and coded stru...
James Davis, Ravi Ramamoorthi, Szymon Rusinkiewicz
We optimize over the set of corrected laplacians (CL) associated with a weighted graph to improve the average case normalized cut (NCut) of a graph. Unlike edge-relaxation SDPs, o...