?This paper presents a computational paradigm called Data-Driven Markov Chain Monte Carlo (DDMCMC) for image segmentation in the Bayesian statistical framework. The paper contribut...
We study the low-level problem of predicting pixel intensities after subpixel image translations. This is a basic subroutine for image warping and super-resolution, and it has a c...
We introduce `Joint Feature Distributions', a general statistical framework for feature based multi-image matching that explicitly models the joint probability distributions ...
Principal Component Analysis (PCA) has been widely used for the representation of shape, appearance, and motion. One drawback of typical PCA methods is that they are least squares...
There is general consensus that context can be a rich source of information about an object's identity, location and scale. However, the issue of how to formalize contextual ...
Conventional vision systems and algorithms assume the camera to have a single viewpoint. However, sensors need not always maintain a single viewpoint. For instance, an incorrectly...
Rahul Swaminathan, Michael D. Grossberg, Shree K. ...