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  Acquiring Robust Representations for Recognition from Image Sequences

Wallraven, C., & Bülthoff, H. (2001). Acquiring Robust Representations for Recognition from Image Sequences. In B. Radig, & S. Florczyk (Eds.), Pattern Recognition: 23rd DAGM Symposium Munich, Germany, September 12–14, 2001 (pp. 216-222). Berlin, Germany: Springer.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-E20E-C Version Permalink: http://hdl.handle.net/21.11116/0000-0005-A873-C
Genre: Conference Paper

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 Creators:
Wallraven, C1, 2, Author              
Bülthoff, HH1, 2, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: We present an object recognition system which is capable of on-line learning of representations of scenes and objects from natural image sequences. Local appearance features are used in a tracking framework to find ‘key-frames’ of the input sequence during learning. In addition, the same basic framework is used for both learning and recognition. The system creates sparse representations and shows good recognition performance in a variety of viewing conditions for a database of natural image sequences.

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 Dates: 2001-09
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1007/3-540-45404-7_29
BibTex Citekey: 1010
 Degree: -

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Title: 23rd DAGM Symposium
Place of Event: München, Germany
Start-/End Date: 2001-09-12 - 2001-09-14

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Source 1

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Title: Pattern Recognition: 23rd DAGM Symposium Munich, Germany, September 12–14, 2001
Source Genre: Proceedings
 Creator(s):
Radig, B, Editor
Florczyk, S, Editor
Affiliations:
-
Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 216 - 222 Identifier: ISBN: 3-540-45404-7

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Title: Lecture Notes in Computer Science
Source Genre: Series
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Publ. Info: -
Pages: - Volume / Issue: 2191 Sequence Number: - Start / End Page: - Identifier: -