Abstract
An object recognition engine needs to extract discriminative features from data representing an object and accurately classify the object to be of practical use in robotics. Furthermore, the classification of the object must be rapidly performed in the presence of a voluminous stream of data. These conditions call for a distributed and scalable architecture that can utilize a cloud computing infrastructure for performing object recognition. This paper introduces a Cloud-based Object Recognition Engine (CORE) to address these needs. CORE is able to train on large-scale datasets, perform classification of 3D point cloud data, and efficiently transfer data in a robotic network.
Original language | English (US) |
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Title of host publication | IROS Hamburg 2015 - Conference Digest |
Subtitle of host publication | IEEE/RSJ International Conference on Intelligent Robots and Systems |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 4512-4517 |
Number of pages | 6 |
ISBN (Electronic) | 9781479999941 |
DOIs | |
State | Published - Dec 11 2015 |
Event | IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015 - Hamburg, Germany Duration: Sep 28 2015 → Oct 2 2015 |
Publication series
Name | IEEE International Conference on Intelligent Robots and Systems |
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Volume | 2015-December |
ISSN (Print) | 2153-0858 |
ISSN (Electronic) | 2153-0866 |
Other
Other | IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015 |
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Country/Territory | Germany |
City | Hamburg |
Period | 9/28/15 → 10/2/15 |
Bibliographical note
Funding Information:This material is based in part upon work supported by the National Science Foundation through grants #IIP- 0934327, #IIS-1017344, #CNS-1061489, #CNS-1138020, #IIP-1332133, #IIS-1427014, and #IIP-1432957.
Publisher Copyright:
© 2015 IEEE.