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CVPR
1999
IEEE
1104views Computer Vision» more  CVPR 1999»
16 years 6 months ago
Geodesic Active Contours for Supervised Texture Segmentation
This paper presents a variational method for supervised texture segmentation, which is based on ideas coming from the curve propagation theory. We assume that a preferable texture...
Nikos Paragios, Rachid Deriche
CGF
2006
94views more  CGF 2006»
15 years 4 months ago
Optimizing Control Variate Estimators for Rendering
We present the Optimizing Control Variate (OCV) estimator, a new estimator for Monte Carlo rendering. Based upon a deterministic sampling framework, OCV allows multiple importance...
Shaohua Fan, Stephen Chenney, Bo Hu, Kam-Wah Tsui,...
142
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TSMC
2008
132views more  TSMC 2008»
15 years 4 months ago
Ensemble Algorithms in Reinforcement Learning
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...
Marco A. Wiering, Hado van Hasselt
IJCV
2006
100views more  IJCV 2006»
15 years 4 months ago
A General Framework for Combining Visual Trackers - The "Black Boxes" Approach
Abstract. Over the past few years researchers have been investigating the enhancement of visual tracking performance by devising trackers that simultaneously make use of several di...
Ido Leichter, Michael Lindenbaum, Ehud Rivlin
CVPR
2007
IEEE
16 years 6 months ago
A Graph Cut Approach to Image Segmentation in Tensor Space
This paper proposes a novel method to apply the standard graph cut technique to segmenting multimodal tensor valued images. The Riemannian nature of the tensor space is explicitly...
Allen Tannenbaum, James G. Malcolm, Yogesh Rathi