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A Bayesian Approach to Learning Single View Generalization in 3D Object Recognition (2003)  (Make Corrections)  
Thomas M. Breuel



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Abstract: Three dimensional vision relies on the ability to generalize from known views of an object to novel views. Of particular interest is the ability of human observers to generalize from a single view of a previously unseen object to novel views. This paper describes a method for achieving single view generalization by modeling conditional densities of the form P (S|B, B # ) or P (B # S) and applying them in a Bayesian decision theoretic framework, where B and B # are two views and S is a... (Update)

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BibTeX entry:   (Update)

@misc{ breuel-bayesian,
  author = "Thomas M. Breuel",
  title = "A Bayesian Approach to Learning Single View Generalization in 3D Object
    Recognition",
  url = "citeseer.ist.psu.edu/article/breuel03bayesian.html" }
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View Based Methods can achieve Bayes-Optimal 3D Recognition - Breuel (2003)   (Correct)
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