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  Nonparametric Density Estimation for Human Pose Tracking

Brox, T., Rosenhahn, B., Kersting, U., & Cremers, D. (2006). Nonparametric Density Estimation for Human Pose Tracking. In Pattern Recognition : 28th DAGM Symposium (pp. 546-555). Berlin, Germany: Springer.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-000F-238C-B Version Permalink: https://hdl.handle.net/11858/00-001M-0000-000F-238E-7
Genre: Conference Paper

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 Creators:
Brox, Thomas, Author
Rosenhahn, Bodo1, Author           
Kersting, Uwe, Author
Cremers, Daniel, Author
Franke, Katrin, Editor
Müller, Klaus-Robert, Editor
Nickolay, Bertram, Editor
Schäfer, Ralf, Editor
Affiliations:
1Computer Graphics, MPI for Informatics, Max Planck Society, ou_40047              

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 Abstract: The present paper considers the supplement of prior knowledge about joint angle configurations in the scope of 3-D human pose tracking. Training samples obtained from an industrial marker based tracking system are used for a nonparametric Parzen density estimation in the 12-dimensional joint configuration space. These learned probability densities constrain the image-driven joint angle estimates by drawing solutions towards familiar configurations. This prevents the method from producing unrealistic pose estimates due to unreliable image cues. Experiments on sequences with a human leg model reveal a considerably increased robustness, particularly in the presence of disturbed images and occlusions. We gratefully acknowledge funding by the DFG project CR250/1 and the Max-Planck Center for visual computing and communication.

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Language(s): eng - English
 Dates: 2007-02-252006
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 314663
Other: Local-ID: C125675300671F7B-106DB5620DA22AFBC125722D0050ACC5-RosenhahnDAGM2006B
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Title: Untitled Event
Place of Event: Berlin, Germany
Start-/End Date: 2006-09-12

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Title: Pattern Recognition : 28th DAGM Symposium
Source Genre: Proceedings
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Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 546 - 555 Identifier: ISBN: 978-3-540-44412-1

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Title: Lecture Notes in Computer Science
Source Genre: Series
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Pages: - Volume / Issue: 4174 Sequence Number: - Start / End Page: - Identifier: -