We present a novel variational approach to top-down image segmentation, which accounts for significant projective transformations between a single prior image and the image to be s...
We present a new shape prior segmentation method using graph cuts capable of segmenting multiple objects. The shape prior energy is based on a shape distance popular with level se...
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...
We propose a novel approach for improving level set seg-
mentation methods by embedding the potential functions
from a discriminatively trained conditional random field
(CRF) in...
Dana Cobzas (University of Alberta), Mark Schmidt ...
Shape symmetry is an important cue for image understanding. In the absence of more detailed prior shape information, segmentation can be significantly facilitated by symmetry. How...