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MVA
2000
136views Computer Vision» more  MVA 2000»
14 years 11 months ago
Qualitative Decomposition of Range Images into Convex Parts / Objects
Previous works on range image segmentation concentrate on surface patches that can be well represented by certain mathematical functions. In this paper we consider the more qualit...
Xiaoyi Jiang
CAIP
2007
Springer
125views Image Analysis» more  CAIP 2007»
15 years 1 months ago
Decomposition for Efficient Eccentricity Transform of Convex Shapes
The eccentricity transform associates to each point of a shape the shortest distance to the point farthest away from it. It is defined in any dimension, for open and closed manyfol...
Adrian Ion, Samuel Peltier, Yll Haxhimusa, Walter ...
DAGM
2008
Springer
14 years 11 months ago
Convex Hodge Decomposition of Image Flows
The total variation (TV) measure is a key concept in the field of variational image analysis. Introduced by Rudin, Osher and Fatemi in connection with image denoising, it also prov...
Jing Yuan, Gabriele Steidl, Christoph Schnörr
CDC
2008
IEEE
124views Control Systems» more  CDC 2008»
15 years 4 months ago
A proximal center-based decomposition method for multi-agent convex optimization
— In this paper we develop a new dual decomposition method for optimizing a sum of convex objective functions corresponding to multiple agents but with coupled constraints. In ou...
Ion Necoara, Johan A. K. Suykens
MP
2006
87views more  MP 2006»
14 years 9 months ago
Convexity and decomposition of mean-risk stochastic programs
Abstract. Traditional stochastic programming is risk neutral in the sense that it is concerned with the optimization of an expectation criterion. A common approach to addressing ri...
Shabbir Ahmed