A Message Passing Algorithm for MRF Inference with Unknown Graphs and Its Applications

被引：0

作者：

Wang, Zhenhua ^{[1
,2
]}

Zhang, Zhiyi ^{[2
]}

Geng, Nan ^{[2
]}

机构：

[1] Univ Adelaide, Sch Comp Sci, Adelaide, SA, Australia

[2] Northwest A&F Univ, Coll Informat Engn, Yangling Dist, Peoples R China

来源：

COMPUTER VISION - ACCV 2014, PT IV | 2015年 / 9006卷

关键词：

D O I：

10.1007/978-3-319-16817-3_19

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Recent research shows that estimating labels and graph structures simultaneously in Markov random Fields can be achieved via solving LP problems. The scalability is a bottleneck that prevents applying such technique to larger problems such as image segmentation and object detection. Here we present a fast message passing algorithm based on the mixed-integer bilinear programming formulation of the original problem. We apply our algorithm to both synthetic data and real-world applications. It compares favourably with previous methods.

引用

页码：288 / 302

页数：15

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