This paper proposes a novel model-guided segmentation framework utilizing a statistical surface wavelet model as a shape prior. In the model building process, a set of training sh...
Yang Li, Tiow Seng Tan, Ihar Volkau, Wieslaw L. No...
We present an over-segmentation based, dense stereo algorithm that jointly estimates segmentation and depth. For mixed pixels on segment boundaries, the algorithm computes foregro...
Yuichi Taguchi, Bennett Wilburn, C. Lawrence Zitni...
Abstract. In this paper we propose a new variational framework for image segmentation that incorporates the information of expected shape and a few points on the boundary into geod...
Yunmei Chen, Weihong Guo, Feng Huang, David Cliffo...
?This paper presents a computational paradigm called Data-Driven Markov Chain Monte Carlo (DDMCMC) for image segmentation in the Bayesian statistical framework. The paper contribut...
Abstract. We apply independent component analysis (ICA) for learning an efficient color image representation of natural scenes. In the spectra of single pixels, the algorithm was a...
Te-Won Lee, Thomas Wachtler, Terrence J. Sejnowski