We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down contr...
Given an arbitrary image, our goal is to segment all distinct
texture subimages. This is done by discovering distinct,
cohesive groups of spatially repeating patterns, called tex...
The widely used denoising algorithms based on nonlinear diffusion, such as Perona-Malik and total variation denoising, modify images toward piecewise constant functions. Though ed...
We study the cosegmentation problem where the objective
is to segment the same object (i.e., region) from a pair
of images. The segmentation for each image can be cast
using a p...
Developing models and methods to manage data vagueness is a current effervescent research field. Some work has been done with supervised problems but unsupervised problems and unce...