We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...
This paper introduces a new method for shape registration by matching vector distance functions. The vector distance function representation is more flexible than the conventional...
We study the influence of numerical conditioning on the accuracy of two closed-form solutions to the overconstrained relative orientation problem. We consider the well known eight...
Automatic annotation is an elegant alternative to explicit recognition in images. In annotation, the image is matched with keyword models, and the most relevant keywords are assig...
We show how to extend the ICP framework to nonrigid registration, while retaining the convergence properties of the original algorithm. The resulting optimal step nonrigid ICP fra...