Abstract
In this paper, we introduce a dictionary learning framework using RGB-D covariance descriptors on point cloud data for performing object classification. Dictionary learning in combination with RGB-D covariance descriptors provides a compact and flexible description of point cloud data. Furthermore, the proposed framework is ideal for updating and sharing dictionaries among robots in a decentralized or cloud network. This work demonstrates the increased performance of 3D object classification utilizing covariance descriptors and dictionary learning over previous results with experiments performed on a publicly available RGB-D database.
| Original language | English (US) |
|---|---|
| Article number | 7139443 |
| Pages (from-to) | 1880-1885 |
| Number of pages | 6 |
| Journal | Proceedings - IEEE International Conference on Robotics and Automation |
| Volume | 2015-June |
| Issue number | June |
| DOIs | |
| State | Published - Jun 29 2015 |
| Event | 2015 IEEE International Conference on Robotics and Automation, ICRA 2015 - Seattle, United States Duration: May 26 2015 → May 30 2015 |
Bibliographical note
Publisher Copyright:© 2015 IEEE.
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