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  A Low-dimensional Representation for Robust Partial Isometric Correspondences Computation

Brunton, A., Wand, M., Wuhrer, S., Seidel, H.-P., & Weinkauf, T. (2014). A Low-dimensional Representation for Robust Partial Isometric Correspondences Computation. Graphical Models, 76(2), 70-85. doi:10.1016/j.gmod.2013.11.003.

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 Urheber:
Brunton, Alan1, Autor           
Wand, Michael1, Autor           
Wuhrer, Stefanie2, Autor
Seidel, Hans-Peter1, Autor           
Weinkauf, Tino1, Autor           
Affiliations:
1Computer Graphics, MPI for Informatics, Max Planck Society, ou_40047              
2External Organizations, ou_persistent22              

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 Zusammenfassung: Intrinsic shape matching has become the standard approach for pose invariant correspondence estimation among deformable shapes. Most existing approaches assume global consistency. While global isometric matching is well understood, only a few heuristic solutions are known for partial matching. Partial matching is particularly important for robustness to topological noise, which is a common problem in real-world scanner data. We introduce a new approach to partial isometric matching based on the observation that isometries are fully determined by local information: a map of a single point and its tangent space fixes an isometry. We develop a new representation for partial isometric maps based on equivalence classes of correspondences between pairs of points and their tangent-spaces. We apply our approach to register partial point clouds and compare it to the state-of-the-art methods, where we obtain significant improvements over global methods for real-world data and stronger guarantees than previous partial matching algorithms.

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Sprache(n): eng - English
 Datum: 2013-12-152014
 Publikationsstatus: Erschienen
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 Identifikatoren: BibTex Citekey: brunton13
DOI: 10.1016/j.gmod.2013.11.003
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Titel: Graphical Models
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: San Diego, CA : Academic Press
Seiten: - Band / Heft: 76 (2) Artikelnummer: - Start- / Endseite: 70 - 85 Identifikator: ISSN: 1524-0703
CoNE: https://pure.mpg.de/cone/journals/resource/954922651186