MIT Libraries homeMIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Efficient incremental map segmentation in dense RGB-D maps

Author(s)
Whelan, Thomas; Kaess, Michael; Finman, Ross Edward; Leonard, John Joseph
Thumbnail
DownloadLeonard_Efficient incremental.pdf (2.928Mb)
OPEN_ACCESS_POLICY

Open Access Policy

Creative Commons Attribution-Noncommercial-Share Alike

Terms of use
Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/
Metadata
Show full item record
Abstract
In this paper we present a method for incrementally segmenting large RGB-D maps as they are being created. Recent advances in dense RGB-D mapping have led to maps of increasing size and density. Segmentation of these raw maps is a first step for higher-level tasks such as object detection. Current popular methods of segmentation scale linearly with the size of the map and generally include all points. Our method takes a previously segmented map and segments new data added to that map incrementally online. Segments in the existing map are re-segmented with the new data based on an iterative voting method. Our segmentation method works in maps with loops to combine partial segmentations from each traversal into a complete segmentation model. We verify our algorithm on multiple real-world datasets spanning many meters and millions of points in real-time. We compare our method against a popular batch segmentation method for accuracy and timing complexity.
Date issued
2014-05
URI
http://hdl.handle.net/1721.1/97582
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science; Massachusetts Institute of Technology. Department of Mechanical Engineering
Journal
Proceedings of the 2014 IEEE International Conference on Robotics and Automation (ICRA)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Finman, Ross, Thomas Whelan, Michael Kaess, and John J. Leonard. “Efficient Incremental Map Segmentation in Dense RGB-D Maps.” 2014 IEEE International Conference on Robotics and Automation (ICRA) (May 2014).
Version: Author's final manuscript
ISBN
978-1-4799-3685-4

Collections
  • MIT Open Access Articles

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries homeMIT Libraries logo

Find us on

Twitter Facebook Instagram YouTube RSS

MIT Libraries navigation

SearchHours & locationsBorrow & requestResearch supportAbout us
PrivacyPermissionsAccessibility
MIT
Massachusetts Institute of Technology
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.