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» Markov Random Field Modeling in Computer Vision
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EMMCVPR
1999
Springer
14 years 1 months ago
Adaptive Bayesian Contour Estimation: A Vector Space Representation Approach
Abstract. We propose a vector representation approach to contour estimation from noisy data. Images are modeled as random elds composed of a set of homogeneous regions contours (bo...
José M. B. Dias
ICCV
2009
IEEE
13 years 6 months ago
Bayesian Poisson regression for crowd counting
Poisson regression models the noisy output of a counting function as a Poisson random variable, with a log-mean parameter that is a linear function of the input vector. In this wo...
Antoni B. Chan, Nuno Vasconcelos
ICPR
2000
IEEE
14 years 10 months ago
Application of Planar Motion Segmentation for Scene Text Extraction
This paper explores an approach for extracting scene text from a sequence of images with relative motion between the camera and the scene. It is assumed that the scene text lies o...
Tarak Gandhi, Rangachar Kasturi, Sameer Antani
ICCV
2007
IEEE
14 years 11 months ago
Probabilistic Color and Adaptive Multi-Feature Tracking with Dynamically Switched Priority Between Cues
We present a probabilistic multi-cue tracking approach constructed by employing a novel randomized template tracker and a constant color model based particle filter. Our approach ...
François Le Clerc, Lionel Oisel, Patrick P&...
ICPR
2010
IEEE
14 years 2 months ago
Motif Discovery and Feature Selection for CRF-Based Activity Recognition
Abstract—Due to their ability to model sequential data without making unnecessary independence assumptions, conditional random fields (CRFs) have become an increasingly popular ...
Liyue Zhao, Xi Wang, Gita Sukthankar