Point cloud registration from local feature correspondences—Evaluation on challenging datasets
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00315550" target="_blank" >RIV/68407700:21230/17:00315550 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1371/journal.pone.0187943" target="_blank" >http://dx.doi.org/10.1371/journal.pone.0187943</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1371/journal.pone.0187943" target="_blank" >10.1371/journal.pone.0187943</a>
Alternative languages
Result language
angličtina
Original language name
Point cloud registration from local feature correspondences—Evaluation on challenging datasets
Original language description
Registration of laser scans, or point clouds in general, is a crucial step of localization and mapping with mobile robots or in object modeling pipelines. A coarse alignment of the point clouds is generally needed before applying local methods such as the Iterative Closest Point (ICP) algorithm. We propose a feature-based approach to point cloud registration and evaluate the proposed method and its individual components on challenging real-world datasets. For a moderate overlap between the laser scans, the method provides a superior registration accuracy compared to state-of-the-art methods including Generalized ICP, 3D Normal-Distribution Transform, Fast Point-Feature Histograms, and 4-Points Congruent Sets. Compared to the surface normals, the points as the underlying features yield higher performance in both keypoint detection and establishing local reference frames. Moreover, sign disambiguation of the basis vectors proves to be an important aspect in creating repeatable local reference frames. A novel method for sign disambiguation is proposed which yields highly repeatable reference frames.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
PLoS ONE
ISSN
1932-6203
e-ISSN
1932-6203
Volume of the periodical
12
Issue of the periodical within the volume
11
Country of publishing house
US - UNITED STATES
Number of pages
16
Pages from-to
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UT code for WoS article
000415121200050
EID of the result in the Scopus database
2-s2.0-85033776560