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» A Markov random field model for term dependencies
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CVPR
2009
IEEE
16 years 5 months ago
Half-integrality based algorithms for Cosegmentation of Images
We study the cosegmentation problem where the objective is to segment the same object (i.e., region) from a pair of images. The segmentation for each image can be cast using a p...
Chuck R. Dyer, Lopamudra Mukherjee, Vikas Singh
TSP
2008
103views more  TSP 2008»
14 years 9 months ago
Low-Rank Variance Approximation in GMRF Models: Single and Multiscale Approaches
Abstract--We present a versatile framework for tractable computation of approximate variances in large-scale Gaussian Markov random field estimation problems. In addition to its ef...
Dmitry M. Malioutov, Jason K. Johnson, Myung Jin C...
EMMCVPR
2005
Springer
15 years 3 months ago
Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study
Abstract. Estimation of parameters of random field models from labeled training data is crucial for their good performance in many image analysis applications. In this paper, we p...
Sanjiv Kumar, Jonas August, Martial Hebert
TIT
2008
132views more  TIT 2008»
14 years 9 months ago
Locally Optimum Detection of Signals in Multiplicative and First-Order Markov Additive Noises
Abstract--In most previously reported studies on locally optimum detection of signals, independent observations have been assumed in various noise environments. The use of an indep...
Jumi Lee, Iickho Song, Hyoungmoon Kwon, Hong Jik K...
ACCV
2006
Springer
15 years 3 months ago
Markovian Framework for Foreground-Background-Shadow Separation of Real World Video Scenes
Abstract. In this paper we give a new model for foreground-background-shadow separation. Our method extracts the faithful silhouettes of foreground objects even if they have partly...
Csaba Benedek, Tamás Szirányi