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» A Fast Probabilistic Bidirectional Texture Function Model
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CGF
2011
12 years 11 months ago
A Sparse Parametric Mixture Model for BTF Compression, Editing and Rendering
Bidirectional texture functions (BTFs) represent the appearance of complex materials. Three major shortcomings with BTFs are the bulky storage, the difficulty in editing and the ...
Hongzhi Wu, Julie Dorsey, Holly E. Rushmeier
IJCV
2006
116views more  IJCV 2006»
13 years 7 months ago
Structure-Texture Image Decomposition - Modeling, Algorithms, and Parameter Selection
This paper explores various aspects of the image decomposition problem using modern variational techniques. We aim at splitting an original image f into two components u and v, whe...
Jean-François Aujol, Guy Gilboa, Tony F. Ch...
SAC
2006
ACM
14 years 1 months ago
Interval-based robust statistical techniques for non-negative convex functions, with application to timing analysis of computer
: In chip design, one of the main objectives is to decrease its clock cycle; however, the existing approaches to timing analysis under uncertainty are based on fundamentally restri...
Michael Orshansky, Wei-Shen Wang, Martine Ceberio,...
ISM
2006
IEEE
277views Multimedia» more  ISM 2006»
13 years 7 months ago
Efficient Bottom-Up Image Segmentation Using Region Competition and the Mumford-Shah Model for Color and Textured Images
Curve evolution implementations [3][23] [25] of the Mumford-Shah functional [16] are of broad interest in image segmentation. These implementations, however, have initialization p...
Yongsheng Pan, J. Douglas Birdwell, Seddik M. Djou...
CVPR
2000
IEEE
14 years 9 months ago
Learning in Gibbsian Fields: How Accurate and How Fast Can It Be?
?Gibbsian fields or Markov random fields are widely used in Bayesian image analysis, but learning Gibbs models is computationally expensive. The computational complexity is pronoun...
Song Chun Zhu, Xiuwen Liu