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AVSS
2006
IEEE
13 years 11 months ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
ACCV
2010
Springer
13 years 2 months ago
Monocular Template-Based Reconstruction of Smooth and Inextensible Surfaces
Abstract. We present different approaches to reconstructing an inextensible surface from point correspondences between an input image and a template image representing a flat refer...
Florent Brunet, Richard I. Hartley, Adrien Bartoli...
PAMI
2007
155views more  PAMI 2007»
13 years 7 months ago
Localization of Shapes Using Statistical Models and Stochastic Optimization
—In this paper, we present a new model for deformations of shapes. A pseudolikelihood is based on the statistical distribution of the gradient vector field of the gray level. The...
François Destrempes, Max Mignotte, Jean-Fra...
MICCAI
2004
Springer
14 years 8 months ago
Learning Coupled Prior Shape and Appearance Models for Segmentation
We present a novel framework for learning a joint shape and appearance model from a large set of un-labelled training examples in arbitrary positions and orientations. The shape an...
Xiaolei Huang, Zhiguo Li, Dimitris N. Metaxas
ISBI
2011
IEEE
12 years 11 months ago
3D segmentation of rodent brain structures using Active Volume Model with shape priors
Object boundary extraction is an important task in brain image analysis. Acquiring detailed 3D representations of the brain structures could improve the detection rate of diseases...
Shaoting Zhang, Junzhou Huang, Mustafa Gökhan...