A New Local Feature Descriptor: Covariant Support Region

被引:0
作者
Liu Yawei [1 ,2 ]
Li Jianwei [1 ]
Zhang Xiaohong [3 ]
机构
[1] Chongqing Univ, Key Lab Optoelect Tech, State Educ Minist, Chongqing 630044, Peoples R China
[2] Chongqing Jiaotong Univ, Inst Optoelect & Informat Tech, Chongqing, Peoples R China
[3] Chongqing Univ, Sch Software Engn, Chongqing 630044, Peoples R China
来源
2009 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND INTELLIGENT SYSTEMS, PROCEEDINGS, VOL 4 | 2009年
关键词
Computer vision; local feature; corner detection; image matching; covariant support region;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Detection and description of Local feature covariant region is a new technology of image contents and image semantic representations, it has become an important foundation of the image recognition, learning and understanding. First, a Laplace of Gaussian corner detection method is proposed based on edge contour, in the meantime, a new local feature descriptor, named covariant support region, is introduced. Then, a detection algorithm of covariant support region is framed, whose covariant properties of rotation and scale are also proved. Comparing with previous studies, the computational complexity is significantly reduced by this method. The data of simulative experiments indicate that the method has good performance on higher accuracy, higher repeatability, and lower complexity.
引用
收藏
页码:346 / +
页数:2
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