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» Markov Random Field Modeling in Computer Vision
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BMVC
2010
13 years 7 months ago
Background Modelling on Tensor Field for Foreground Segmentation
The paper proposes a new method to perform foreground detection by means of background modeling using the tensor concept. Sometimes, statistical modelling directly on image values...
Rui Caseiro, Jorge Batista, Pedro Martins
3DIM
2005
IEEE
14 years 2 months ago
A MRF Formulation for Coded Structured Light
Multimedia projectors and cameras make possible the use of structured light to solve problems such as 3D reconstruction, disparity map computation and camera or projector calibrat...
Jean-Philippe Tardif, Sébastien Roy
NAACL
2010
13 years 7 months ago
Minimally-Supervised Extraction of Entities from Text Advertisements
Extraction of entities from ad creatives is an important problem that can benefit many computational advertising tasks. Supervised and semi-supervised solutions rely on labeled da...
Sameer Singh, Dustin Hillard, Chris Leggetter
AUSAI
2009
Springer
14 years 3 months ago
Information-Theoretic Image Reconstruction and Segmentation from Noisy Projections
The minimum message length (MML) principle for inductive inference has been successfully applied to image segmentation where the images are modelled by Markov random fields (MRF)....
Gerhard Visser, David L. Dowe, Imants D. Svalbe
ICPR
2000
IEEE
14 years 10 months ago
Statistical Motion-Based Object Indexing Using Optic Flow Field
In this paper, we propose an original approach for content-based video indexing and retrieval. It relies on the tracking of entities of interest and the analysis of their apparent...
Ronan Fablet, Patrick Bouthemy