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» A New Bayesian Method for Range Image Segmentation
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ICIP
2004
IEEE
16 years 4 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
16 years 3 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
15 years 29 days 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
15 years 9 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
16 years 3 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