Lucas-Kanade algorithm with GNC

被引：0
|
作者：
Junghans, M [1 ]
Leich, A [1 ]
Jentschel, HJ [1 ]
机构：
[1] Dresden Univ Technol, D-8027 Dresden, Germany
来源：
2004 7TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, VOLS 1-3 | 2004年
关键词：
Lucas-Kanade; GNC coarse-to-fine; Euclidean distance;
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：
The similarity of two arbitrary real functions can be analysed calculating the squared Euclidean distance.. the parameter space. The application of this method to digital images was proposed by Lucas and kanade. In this paper the concept of Graduared Non-Convexity (GNC) is applied to the problem of evaluating the parameter function. It is shown, that the application of GNC to the parameter function and the construction and evaluation of a pyramid of spatially smooth and sub-sampled images are equivalent operations in particular, but practically relevant cases.
引用
收藏
页码：1088 / 1091
页数：4
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