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16 years 10 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li
ICDAR
2009
IEEE
14 years 9 months ago
Stochastic Segment Modeling for Offline Handwriting Recognition
In this paper, we present a novel approach for incorporating structural information into the hidden Markov Modeling (HMM) framework for offline handwriting recognition. Traditiona...
Premkumar Natarajan, Krishna Subramanian, Anurag B...
CVPR
2008
IEEE
16 years 1 months ago
Graph-shifts: Natural image labeling by dynamic hierarchical computing
In this paper, we present a new approach for image labeling based on the recently introduced graph-shifts algorithm. Graph-shifts is an energy minimization algorithm that does lab...
Jason J. Corso, Alan L. Yuille, Zhuowen Tu
ECCV
2008
Springer
16 years 1 months ago
Understanding Camera Trade-Offs through a Bayesian Analysis of Light Field Projections
Computer vision has traditionally focused on extracting structure, such as depth, from images acquired using thin-lens or pinhole optics. The development of computational imaging i...
Anat Levin, William T. Freeman, Frédo Duran...
CVPR
2012
IEEE
13 years 2 months ago
Light field denoising, light field superresolution and stereo camera based refocussing using a GMM light field patch prior
With the recent availability of commercial light field cameras, we can foresee a future in which light field signals will be as common place as images. Hence, there is an immine...
Kaushik Mitra, Ashok Veeraraghavan