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» Bayesian Structure from Motion
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126
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AI
2008
Springer
15 years 2 months ago
Conditional independence and chain event graphs
Graphs provide an excellent framework for interrogating symmetric models of measurement random variables and discovering their implied conditional independence structure. However,...
Jim Q. Smith, Paul E. Anderson
171
Voted
CVPR
2009
IEEE
16 years 9 months ago
Learning Visual Flows: A Lie Algebraic Approach
We present a novel method for modeling dynamic visual phenomena, which consists of two key aspects. First, the in- tegral motion of constituent elements in a dynamic scene is ca...
Dahua Lin, W. Eric L. Grimson, John W. Fisher III
126
Voted
AROBOTS
2005
88views more  AROBOTS 2005»
15 years 2 months ago
Head Movements for Depth Perception: Praying Mantis versus Pigeon
Abstract. Inspired by the abilities of both the praying mantis and the pigeon to judge distance by use of motionbased visually mediated odometry, we create miniature models for dep...
Alfred M. Bruckstein, Robert J. Holt, Igor Katsman...
ICCV
2007
IEEE
16 years 4 months ago
Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
135
Voted
RECOMB
2003
Springer
16 years 2 months ago
Modeling dependencies in protein-DNA binding sites
The availability of whole genome sequences and high-throughput genomic assays opens the door for in silico analysis of transcription regulation. This includes methods for discover...
Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kap...