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» A probabilistic framework for image segmentation
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CVPR
2007
IEEE
14 years 9 months ago
Regression tracking with data relevance determination
This paper 1 addresses the problem of efficient visual 2D template tracking in image sequences. We adopt a discriminative approach in which the observations at each frame yield di...
Ioannis Patras, Edwin R. Hancock
ECCV
2002
Springer
14 years 9 months ago
Understanding and Modeling the Evolution of Critical Points under Gaussian Blurring
Abstract. In order to investigate the deep structure of Gaussian scale space images, one needs to understand the behaviour of critical points under the influence of parameter-drive...
Arjan Kuijper, Luc Florack
CVPR
2009
IEEE
15 years 3 months ago
Nonparametric Scene Parsing: Label Transfer via Dense Scene Alignment
In this paper we propose a novel nonparametric approach for object recognition and scene parsing using dense scene alignment. Given an input image, we retrieve its best matches ...
Antonio B. Torralba, Ce Liu, Jenny Yuen
CVPR
2006
IEEE
14 years 9 months ago
Supervised Learning of Edges and Object Boundaries
Edge detection is one of the most studied problems in computer vision, yet it remains a very challenging task. It is difficult since often the decision for an edge cannot be made ...
Piotr Dollár, Zhuowen Tu, Serge Belongie
CVPR
2008
IEEE
14 years 9 months ago
Learning for stereo vision using the structured support vector machine
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
Yunpeng Li, Daniel P. Huttenlocher