A quantitative evaluation of surface normal estimation in point clouds

Krzysztof Jordan, Philippos Mordohai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

47 Scopus citations

Abstract

We revisit a well-studied problem in the analysis of range data: surface normal estimation for a set of unorganized points. Surface normal estimation has been well-studied initially due to its theoretical appeal and more recently due to its many practical applications. The latter cover several aspects of range data analysis from plane or surface fitting to segmentation, object detection and scene analysis. Following the vast majority of the literature, we also focus our attention on techniques that operate in small neighborhoods around the point whose normal is to be estimated. We pay close attention to aspects of the implementation, such as the use of weights and normalization, that have not been studied in detail in the past. We perform quantitative evaluation on a diverse set of point clouds derived from 3D meshes, which allows us to obtain accurate ground truth.

Original languageEnglish
Title of host publicationIROS 2014 Conference Digest - IEEE/RSJ International Conference on Intelligent Robots and Systems
Pages4220-4226
Number of pages7
ISBN (Electronic)9781479969340
DOIs
StatePublished - 31 Oct 2014
Event2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014 - Chicago, United States
Duration: 14 Sep 201418 Sep 2014

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014
Country/TerritoryUnited States
CityChicago
Period14/09/1418/09/14

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