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Cited by 559

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Multiview registration for large data sets

Pulli, K.·2003·Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062)

Abstract

We present a multiview registration method for aligning range data. We first align scans pairwise with each other and use the pairwise alignments as constraints that the multiview step enforces while evenly diffusing the pairwise registration errors. This approach is especially suitable for registering large data sets, since using constraints from pairwise alignments does not require loading the entire data set into memory to perform the alignment. The alignment method is efficient, and it is less likely to get stuck into a local minimum than previous methods, and can be used in conjunction with any pairwise method based on aligning overlapping surface sections.

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Metadata

Authors
Pulli, K.
Venue
Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062)
Published
2003-01-20
Pages
160-168
OpenAlex
W1603720607
Cited by
559
References
1
FWCI
87.66
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Multiview registration for large data sets. https://app.cochat.ai/papers/10.1109/im.1999.805346
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Pulli, K. (2003). Multiview registration for large data sets. Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062). https://doi.org/10.1109/im.1999.805346

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