Object Classification Using Dictionary Learning and RGB-D Covariance Descriptors

被引:0
|
作者
Beksi, William J. [1 ]
Papanikolopoulos, Nikolaos [1 ]
机构
[1] Univ Minnesota, Dept Comp Sci & Engn, Minneapolis, MN USA
关键词
SPARSE; RECOGNITION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1880 / 1885
页数:6
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