A Fast Annotation Model Based on Visual Concept Distribution
Dong Lin Cao, Xian Ming Lin, Da Zhen Lin · Applied Mechanics and Materials · 2013
Image annotation is one of the important technologies in image retrieval and semantic analysis. To overcome the estimation and efficiency problem in CMRM model, we proposed a Visual Concept Distribution based annotation model which estimates the probability through the Visual Concept Set. Experiment results shows that our approach outperforms three classical annotation models (CMRM, CRM and PLSA-WORDS) and closes to the complicated PLSA-FUSION model.