Abstract
In This paper, we introduce a new covariance based feature descriptor To be used on 'colored' point clouds gathered by a mobile robot equipped with an RGB-D camera. Although many recent descriptors provide adequate results, There is not yet a clear consensus on how To best Tackle 'colored' point clouds. We present The notion of a covariance on RGB-D data. Covariances have not only been proven To be successful in image processing, but in other domains as well. Their main advantage is That They provide a compact and flexible description of point clouds. Our work is a first step Towards demonstrating The usability of The concept of covariances in conjunction with RGB-D data. Experiments performed on an RGB-D database and compared To previous results show The increased performance of our method.
Original language | English (US) |
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Title of host publication | Proceedings - IEEE International Conference on Robotics and Automation |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 5467-5472 |
Number of pages | 6 |
ISBN (Electronic) | 9781479936854, 9781479936854 |
DOIs | |
State | Published - Sep 22 2014 |
Event | 2014 IEEE International Conference on Robotics and Automation, ICRA 2014 - Hong Kong, China Duration: May 31 2014 → Jun 7 2014 |
Publication series
Name | Proceedings - IEEE International Conference on Robotics and Automation |
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ISSN (Print) | 1050-4729 |
Other
Other | 2014 IEEE International Conference on Robotics and Automation, ICRA 2014 |
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Country/Territory | China |
City | Hong Kong |
Period | 5/31/14 → 6/7/14 |
Bibliographical note
Publisher Copyright:© 2014 IEEE.