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Report (Bericht) zugänglich unter
URN: urn:nbn:de:bsz:291-scidok-36912
URL: http://scidok.sulb.uni-saarland.de/volltexte/2011/3691/


Self-adapting structuring and representation of space

Dengel, Andreas

Quelle: (1991) Kaiserslautern ; Saarbrücken : DFKI, 1991
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Dokument 1.pdf (207 KB)

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SWD-Schlagwörter: Künstliche Intelligenz
Institut: DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
DDC-Sachgruppe: Informatik
Dokumentart: Report (Bericht)
Schriftenreihe: Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x]
Bandnummer: 91-22
Sprache: Englisch
Erstellungsjahr: 1991
Publikationsdatum: 28.06.2011
Kurzfassung auf Englisch: The objective of this report is to propose a syntactic formalism for space representation. Beside the well known advantages of hierarchical data structure, the underlying approach has the additional strength of self-adapting to a spatial structure at hand. The formalism is called puzzletree because its generation results in a number of blocks which in a certain order -- like a puzzle - reconstruct the original space. The strength of the approach does not lie only in providing a compact representation of space (e.g. high compression), but also in attaining an ideal basis for further knowledge-based modeling and recognition of objects. The approach may be applied to any higher-dimensioned space (e.g. images, volumes). The report concentrates on the principles of puzzletrees by explaining the underlying heuristic for their generation with respect to 2D spaces, i.e. images, but also schemes their application to volume data. Furthermore, the paper outlines the use of puzzletrees to facilitate higher-level operations like image segmentation or object recognition. Finally, results are shown and a comparison to conventional region quadtrees is done.
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