Scene understanding by rule evaluation

被引:8
作者
Bischoff, WF [1 ]
Caelli, T [1 ]
机构
[1] CURTIN UNIV TECHNOL,SCH COMP,GPO BOX U1987,PERTH,WA 6001,AUSTRALIA
关键词
conditional rule generation; machine learning; object recognition; scene understanding; visual learning;
D O I
10.1109/34.632987
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We consider how machine learning can be used to help solve the problem of identifying objects or structures composed of parts in complex scenes. We first discuss a conditional rule generation technique (CRG) that is designed to describe structures using part attributes and their relations. We then show how the resultant rules can be used for region labeling and examine constraint propagation techniques for improving rule-based object classification.
引用
收藏
页码:1284 / 1288
页数:5
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