Human motion tracking is an important problem in computer vision. Most prior approaches have concentrated on efficient inference algorithms and prior motion models; however, few c...
Marek Vondrak, Leonid Sigal, Odest Chadwicke Jenki...
We present a viewpoint-based approach for the quick fusion of multiple stereo depth maps. Our method selects depth estimates for each pixel that minimize violations of visibility ...
Paul Merrell, Amir Akbarzadeh, Liang Wang, Philipp...
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...
In this paper we consider the problem of solving different pose and registration problems under rotational constraints. Traditionally, methods such as the iterative closest point ...