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https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1007/115957...
Part of book or chapter of book . 2005 . Peer-reviewed
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DBLP
Conference object . 2020
Data sources: DBLP
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3D Shape from Unorganized 3D Point Clouds

Authors: George I. Kamberov; Gerda Kamberova; Amit Jain;

3D Shape from Unorganized 3D Point Clouds

Abstract

We present a framework to automatically infer topology and geometry from an unorganized 3D point cloud obtained from a 3D scene. If the cloud is not oriented, we use existing methods to orient it prior to recovering the topology. We develop a quality measure for scoring a chosen topology/orientation. The topology is used to segment the cloud into manifold components and later in the computation of shape descriptors.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Top 10%
Average
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