2D conditional random fields for image classification

被引：0

作者：

Wen, Ming ^{[1
]}

Han, Hui ^{[1
]}

Wang, Lu ^{[1
]}

Wang, Wenyuan ^{[1
]}

机构：

[1] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China

来源：

INTELLIGENT INFORMATION PROCESSING III | 2006年 / 228卷

关键词：

multimedia data mining; image classification; 2D conditional random fields; loopy belief propagation;

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：

For grid-based image classification, an image is divided into blocks, and a feature vector is formed for each block. Conventional grid-based classification algorithms suffer from inability to take into account the two-dimensional neighborhood interactions of blocks. We present a classification method based on two-dimensional Conditional Random Fields which can avoid the limitation. As a discriminative approach, the proposed method offers several advantages over generative approaches, including the ability to relax the assumption of conditional independence of the observations.

引用

页码：383 / +

页数：2

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