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 :
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