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» Light Fields and Computational Imaging
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IPMI
2005
Springer
15 years 11 months ago
Extrapolation of Sparse Tensor Fields: Application to the Modeling of Brain Variability
Modeling the variability of brain structures is a fundamental problem in the neurosciences. In this paper, we start from a dataset of precisely delineated anatomical structures in ...
Pierre Fillard, Vincent Arsigny, Xavier Pennec, Pa...
ECCV
2006
Springer
15 years 12 months ago
A Comparative Study of Energy Minimization Methods for Markov Random Fields
One of the most exciting advances in early vision has been the development of efficient energy minimization algorithms. Many early vision tasks require labeling each pixel with som...
Richard Szeliski, Ramin Zabih, Daniel Scharstein, ...
EMMCVPR
2007
Springer
15 years 4 months ago
Bayesian Inference for Layer Representation with Mixed Markov Random Field
Abstract. This paper presents a Bayesian inference algorithm for image layer representation [26], 2.1D sketch [6], with mixed Markov random field. 2.1D sketch is an very important...
Ru-Xin Gao, Tianfu Wu, Song Chun Zhu, Nong Sang
ICCV
2009
IEEE
16 years 3 months ago
Structure- and Motion-adaptive Regularization for High Accuracy Optic Flow
The accurate estimation of motion in image sequences is of central importance to numerous computer vision applications. Most competitive algorithms compute flow fields by minimi...
Andreas Wedel, Daniel Cremers, Thomas Pock, Horst ...
IMAGING
2000
14 years 11 months ago
Shadow Identification using Colour Ratios
In this paper we present a comprehensive method for identifying probable shadow regions in an image. Doing so is relevant to computer vision, colour constancy, and image reproduct...
Kobus Barnard, Graham D. Finlayson