Sciweavers

Share
ICMCS
2007
IEEE

A Probability Model for Image Annotation

9 years 1 months ago
A Probability Model for Image Annotation
Automatic image annotation is a promising solution to enable more effective image retrieval by keywords. Traditionally, statistical models for image auto-annotation predicate each annotated keyword independently without considering the correlation of words. In this paper, we propose a novel probability model, in which the correspondence between keywords and image visual tokens/regions and the word-to-word correlation are well combined. We employ the conditional probability to express two kinds of correlation uniformly and obtain the correspondence between keyword and visual feature with the cross-media relevance model (CMRM). Experiments conducted on standard Corel dataset demonstrate the effectiveness of the proposed method for image automatic annotation.
Yong Ge, Richang Hong, Zhiwei Gu, Rong Zhang, Xiuq
Added 08 Dec 2010
Updated 08 Dec 2010
Type Conference
Year 2007
Where ICMCS
Authors Yong Ge, Richang Hong, Zhiwei Gu, Rong Zhang, Xiuqing Wu
Comments (0)
books