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ICMCS
2006
IEEE

Automatic Semantic Annotation of Images using Spatial Hidden Markov Model

14 years 8 days ago
Automatic Semantic Annotation of Images using Spatial Hidden Markov Model
This paper presents a new spatial-HMM(SHMM)for automatically classifying and annotating natural images. Our model is a 2D generalization of the traditional HMM in the sense that both vertical and horizontal transitions between hidden states are taken into consideration. The three basic problems with HMM-liked model are also solved in our model. Given a sequence of visual features, our model automatically derives annotations from keywords associated with the most appropriate concept class, and with no need of a pre-defined length threshold. Our experiments showed that our model outperformed the previous 2D MHMM in recognition accuracy and also achieved a high annotation accuracy.
Feiyang Yu, Horace Ho-Shing Ip
Added 11 Jun 2010
Updated 11 Jun 2010
Type Conference
Year 2006
Where ICMCS
Authors Feiyang Yu, Horace Ho-Shing Ip
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