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|a DE-627
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|e rakwb
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|a eng
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| 100 |
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|a Shokoufandeh, Ali
|e verfasserin
|4 aut
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|a Indexing hierarchical structures using graph spectra
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|c 2005
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|a Text
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|a ohne Hilfsmittel zu benutzen
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|2 rdacarrier
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|a Date Completed 11.08.2005
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|a Date Revised 10.12.2019
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|a published: Print
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|a Citation Status MEDLINE
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|a Hierarchical image structures are abundant in computer vision and have been used to encode part structure, scale spaces, and a variety of multiresolution features. In this paper, we describe a framework for indexing such representations that embeds the topological structure of a directed acyclic graph (DAG) into a low-dimensional vector space. Based on a novel spectral characterization of a DAG, this topological signature allows us to efficiently retrieve a promising set of candidates from a database of models using a simple nearest-neighbor search. We establish the insensitivity of the signature to minor perturbation of graph structure due to noise, occlusion, or node split/merge. To accommodate large-scale occlusion, the DAG rooted at each nonleaf node of the query "votes" for model objects that share that "part," effectively accumulating local evidence in a model DAG's topological subspaces. We demonstrate the approach with a series of indexing experiments in the domain of view-based 3D object recognition using shock graphs
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|a Comparative Study
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|a Evaluation Study
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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| 650 |
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|a Research Support, U.S. Gov't, Non-P.H.S.
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| 700 |
1 |
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|a Macrini, Diego
|e verfasserin
|4 aut
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| 700 |
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|a Dickinson, Sven
|e verfasserin
|4 aut
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| 700 |
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|a Siddiqi, Kaleem
|e verfasserin
|4 aut
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| 700 |
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|a Zucker, Steven W
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 27(2005), 7 vom: 01. Juli, Seite 1125-40
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnns
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|g volume:27
|g year:2005
|g number:7
|g day:01
|g month:07
|g pages:1125-40
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