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  Learning Dense 3D Correspondence

Steinke, F., Schölkopf, B., & Blanz, V. (2007). Learning Dense 3D Correspondence. In B. Schölkopf, J. Platt, & T. Hoffman (Eds.), Advances in Neural Information Processing Systems 19 (pp. 1313-1320). Cambridge, MA, USA: MIT Press.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-CBEB-C Version Permalink: http://hdl.handle.net/21.11116/0000-0002-E211-B
Genre: Conference Paper

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 Creators:
Steinke, F1, 2, Author              
Schölkopf, B1, 2, Author              
Blanz, V2, 3, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              
3Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              

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 Abstract: Establishing correspondence between distinct objects is an important and nontrivial task: correctness of the correspondence hinges on properties which are difficult to capture in an a priori criterion. While previous work has used a priori criteria which in some cases led to very good results, the present paper explores whether it is possible to learn a combination of features that, for a given training set of aligned human heads, characterizes the notion of correct correspondence. By optimizing this criterion, we are then able to compute correspondence and morphs for novel heads.

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 Dates: 2007-09
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 4148
 Degree: -

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Title: Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006)
Place of Event: Vancouver, BC, Canada
Start-/End Date: 2006-12-04 - 2006-12-07

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Title: Advances in Neural Information Processing Systems 19
Source Genre: Proceedings
 Creator(s):
Schölkopf, B1, Editor            
Platt, JC, Editor
Hoffman, T, Editor
Affiliations:
1 Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795            
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1313 - 1320 Identifier: ISBN: 0-262-19568-2