Part Segmentation for Object Recognition

被引：22
|
作者：
Pentland, Alex [1 ]
机构：
[1] MIT, Media Lab, Vis Sci Grp, Room E15-410,20 Ames St, Cambridge, MA 02139 USA
来源：
NEURAL COMPUTATION | 1989年 / 1卷 / 01期
基金：
美国国家科学基金会;
关键词：
D O I：
10.1162/neco.1989.1.1.82
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Visual object recognition is a difficult problem that has been solved by biological visual systems. An approach to object recognition is described in which the image is segmented into parts using two simple, biologically-plausible mechanisms: a filtering operation to produce a large set of potential object "parts," followed by a new type of network that searches among these part hypotheses to produce the simplest, most likely description of the image's part structure.
引用
收藏
页码：82 / 91
页数：10
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