— In this paper, a de-interlacing algorithm to find the optimal deinterlaced results given accuracy-limited motion information is proposed. The de-interlacing process is formula...
We propose a methodology for improved segmentation of images in a Bayesian framework by fusion of color, texture and gradient information. The proposed algorithm is initialized by...
In this paper, we propose a unified graphical-model framework to interpret a scene composed of multiple objects in monocular video sequences. Using a single pairwise Markov random...
In this paper we describe a new method for improving the representation of textures in blends of multiple images based on a Markov Random Field (MRF) algorithm. We show that direc...
We describe results on combining depth information from a laser range-finder and color and texture image cues to segment ill-structured dirt, gravel, and asphalt roads as input t...