222 search results - page 33 / 45 » Self-Validated Labeling of Markov Random Fields for Image Se... |
MICCAI
2010
Springer
13 years 6 months ago
2010
Springer
We present a new non-parametric model constraint graph min-cut algorithm for automatic kidney segmentation in CT images. The segmentation is formulated as a maximum a-posteriori es...
MICCAI
2010
Springer
13 years 5 months ago
2010
Springer
Abstract. Deformable surface models are often represented as triangular meshes in image segmentation applications. For a fast and easily regularized deformation onto the target obj...
EMMCVPR
2005
Springer
2005
Springer
Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study
14 years 1 months ago
Abstract. Estimation of parameters of random field models from labeled training data is crucial for their good performance in many image analysis applications. In this paper, we p...
WACV
2007
IEEE
14 years 2 months ago
2007
IEEE
We present a method for the simultaneous detection and segmentation of objects from static images. We employ lowlevel contour features that enable us to learn the coarse object sh...
ICIP
2005
IEEE
14 years 9 months ago
2005
IEEE
In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...