Feature Descriptors: a Review of Multiple Cues Approaches

被引:1
|
作者
Pham, Cuong H. [1 ]
Yaguchi, Yuichi [1 ]
Naruse, Keitaro [1 ]
机构
[1] Univ Aizu, Grad Sch Comp & Informat Syst, Aizu Wakamatsu, Fukushima, Japan
关键词
ROBUST;
D O I
10.1109/CIT.2016.61
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Feature descriptors have been playing an important role in many computer vision problems, such as image matching and object recognition. While classic descriptors using texture or shape as a single cue of descriptive information have been proved to be successful, recently, several approaches have been proposed introducing the combination of multiple cues to increase descriptive power and robustness. In this paper, we review the methodology of the most recent and popular multiple cues descriptors, and evaluate them with respect to their application and robustness to the variance of conditions.
引用
收藏
页码:310 / 315
页数:6
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