development is a highly abstract process that requires intense concentration. The authors show that interrupting this process can significantly reduce a developer’s efficiency an...
Many problems in computer vision can be modeled using
conditional Markov random fields (CRF). Since finding
the maximum a posteriori (MAP) solution in such models
is NP-hard, mu...
Stephen Gould (Stanford University), Fernando Amat...
This paper addresses the problem of computing visual hulls from image contours. We propose a new hybrid approach which overcomes the precision-complexity trade-off inherent to vox...
Automatic image categorization using low-level features is a challenging research topic in computer vision. In this paper, we formulate the image categorization problem as a multi...
We present an algorithm to reduce per-pixel search ranges for Markov Random Fields-based stereo algorithms. Our algorithm is based on the intuitions that reliably matched pixels ne...