DocumentCode
716407
Title
Object classification using dictionary learning and RGB-D covariance descriptors
Author
Beksi, William J. ; Papanikolopoulos, Nikolaos
Author_Institution
Dept. of Comput. Sci. & Eng., Univ. of Minnesota, Minneapolis, MN, USA
fYear
2015
fDate
26-30 May 2015
Firstpage
1880
Lastpage
1885
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.
Keywords
image classification; image colour analysis; learning (artificial intelligence); object recognition; robot vision; RGB-D covariance descriptors; cloud network; computer vision; decentralized network; dictionary learning framework; dictionary sharing; dictionary updating; object classification; object recognition; point cloud data; robotics; Covariance matrices; Databases; Dictionaries; Robots; Shape; Three-dimensional displays; Visualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Automation (ICRA), 2015 IEEE International Conference on
Conference_Location
Seattle, WA
Type
conf
DOI
10.1109/ICRA.2015.7139443
Filename
7139443
Link To Document