Automatic Image Annotation Based On Vocabulary Prior Probability
Automatic image annotation is an important and challenging task in computer vision. The existing models only use low-levels features of images to do the approximate calculation, without considering the influence of semantic information. This paper proposes a new automatic image annotation algorithm based on the vocabulary prior probability It can solve the semantic gap to a certain extent. The algorithm is divided into two stages, first according to the existing generative model calculated the initial annotation word, and then calculated image similarity with considering the annotated words to improve the result of the annotation. The experiments over Corel5k images have shown the proposed method can effectively improve the rate of the annotations accurac) and recall.
Image annotation Generative model Vocabulary prior probability Image retrieval
Zongyu Lan Shaozi Li Donglin Cao Xiao Ke
Cognitive Science Department of Xiamen University, Xiamen,361005 Fujian Key Laboratory of the Brain-like Intelligent Systems( Xiamen University),Xiamen,36I005
国际会议
厦门
英文
720-724
2010-10-29（万方平台首次上网日期，不代表论文的发表时间）