Completion energies and scale

被引:7
作者
Sharon, E
Brandt, A
Basri, R
机构
来源
1997 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS | 1997年
关键词
D O I
10.1109/CVPR.1997.609432
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The detection of smooth curves in images and their completion over gaps are two important problems in perceptual grouping. lit this paper we examine the nation of completion energy and introduce a fast method to compute the most likely completions in images. Specifically, we develop two novel analytic approximations to the curve of least energy. In addition, we introduce a fast numerical method to compute the curve of least energy and show that our approximations are obtained at early stages of this numerical computation. We then use our newly developed energies to find the most likely completions in images through a generalized summation of induction fields. Since in practice edge elements are obtained by applying filters of certain widths and lengths to the image, we adjust our computation to take these parameters into account. Finally, we show that, due to the smoothness of the kernel of summation the process of summing induction fields can be run in time that is linear in the number of different edge elements in the image, or in O(N log N) where N is the number of pixels in the image, using multigrid methods.
引用
收藏
页码:884 / 890
页数:7
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