TY - JOUR
T1 - Object classification using dictionary learning and RGB-D covariance descriptors
AU - Beksi, William J.
AU - Papanikolopoulos, Nikolaos P
PY - 2015/1/1
Y1 - 2015/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84938234038&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84938234038&partnerID=8YFLogxK
U2 - 10.1109/ICRA.2015.7139443
DO - 10.1109/ICRA.2015.7139443
M3 - Article
AN - SCOPUS:84938234038
VL - 2015-June
SP - 1880
EP - 1885
JO - Proceedings - IEEE International Conference on Robotics and Automation
JF - Proceedings - IEEE International Conference on Robotics and Automation
SN - 1050-4729
IS - June
M1 - 7139443
ER -