In this work, we present a technique for robust estimation, which by explicitly incorporating the inherent uncertainty of the estimation procedure, results in a more efficient rob...
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
We present a novel representation for modeling textured regions subject to smooth variations in orientation and scale. Utilizing the steerable pyramid of Simoncelli and Freeman as...
We show that multi-path analysis using images from a timeof-flight (ToF) camera provides a tantalizing opportunity to infer about 3D geometry of not only visible but hidden parts ...
Ahmed Kirmani, Tyler Hutchison, James Davis, Rames...
We propose an algorithm which can jointly estimate camera pose and point set registration. Given point sets from two views of a stationary scene, our algorithm registers the point...
In this work we revisit the Mumford-Shah functional, one of the most studied variational approaches to image segmentation. The contribution of this paper is to propose an algorith...
Thomas Pock, Daniel Cremers, Horst Bischof, Antoni...
Geometric verification with RANSAC has become a crucial step for many local feature based matching applications. Therefore, the details of its implementation are directly relevant...
With the rise of photo-sharing websites such as Facebook and Flickr has come dramatic growth in the number of photographs online. Recent research in object recognition has used su...
Yunpeng Li, David J. Crandall, Daniel P. Huttenloc...
Within the field of action recognition, features and descriptors are often engineered to be sparse and invariant to transformation. While sparsity makes the problem tractable, it ...
In this paper, we propose multivariate tensor-based surface morphometry, a new method for surface analysis, using holomorphic differentials; we also apply it to study brain anatom...
Yalin Wang, Tony F. Chan, Arthur W. Toga, Paul M. ...