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...
Usually, the stereo correspondence for a feature point in the first image is obtained by searching in a predefined region of the second image, based on the epipolar line and the m...
This paper presents an algorithm for order reduction of
factors in High-Order Markov Random Fields (HOMRFs).
Standard techniques for transforming arbitrary high-order
factors in...
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
The scene flow in binocular stereo setup is estimated using a seed growing algorithm. A pair of calibrated and synchronized cameras observe a scene and output a sequence of image...