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» A New Bayesian Method for Range Image Segmentation
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ICIP
2004
IEEE
14 years 9 months ago
Unsupervised motion detection using a markovian temporal model with global spatial constraints
In this work, we propose an unsupervised Bayesian model for the detection of moving objects from dynamic scenes. This unsupervised solution is a three-step approach that uses a st...
Pierre-Marc Jodoin, Max Mignotte
ICIAP
2005
ACM
14 years 7 months ago
A New Efficient Method for Producing Global Affine Invariants
This paper introduces a new efficient way for computing affine invariant features from gray-scale images. The method is based on a novel image transform which produces infinitely m...
Esa Rahtu, Janne Heikkilä, Mikko Salo
ICIP
2010
IEEE
13 years 5 months ago
Reducing graphs in graph cut segmentation
In few years, graph cuts have become a leading method for solving a wide range of problems in computer vision. However, graph cuts involve the construction of huge graphs which so...
Nicolas Lerme, François Malgouyres, Lucas L...
EMMCVPR
2007
Springer
14 years 1 months ago
Bayesian Order-Adaptive Clustering for Video Segmentation
Video segmentation requires the partitioning of a series of images into groups that are both spatially coherent and smooth along the time axis. We formulate segmentation as a Bayes...
Peter Orbanz, Samuel Braendle, Joachim M. Buhmann
MICCAI
2003
Springer
14 years 8 months ago
A Statistically Based Surface Evolution Method for Medical Image Segmentation: Presentation and Validation
Abstract. In this paper we present a new algorithm for 3D medical image segmentation. The algorithm is fast, relatively simple to implement, and semi-automatic. It is based on mini...
Eric Pichon, Allen Tannenbaum, Ron Kikinis