We present a variational Bayesian framework for performing inference, density estimation and model selection in a special class of graphical models--Hidden Markov Random Fields (H...
Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang
Purely bottom-up, unsupervised segmentation of a single
image into two segments remains a challenging task for
computer vision. The co-segmentation problem is the process
of joi...
Extracting object boundaries in thermal images is a challenging task because of the amorphous nature of the images and the lack of sharp boundaries. Classical edge-based segmentat...
Abstract. This paper presents a novel approach to unsupervised texture segmentation that relies on a very general nonparametric statistical model of image neighborhoods. The method...
Accurate bone modeling from medical images is essential in the diagnosis and treatment of patients because it supports the detection of abnormal bone morphology, which is often re...