DocumentCode :
3439032
Title :
Automatic image annotation based on vocabulary prior probability
Author :
Lan, Zongyu ; Li, Shaozi ; Cao, Donglin ; Ke, Xiao
Author_Institution :
Cognitive Sci. Dept., Xiamen Univ., Xiamen, China
Volume :
3
fYear :
2010
fDate :
29-31 Oct. 2010
Firstpage :
720
Lastpage :
724
Abstract :
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 annotation´s accuracy and recall.
Keywords :
computer vision; feature extraction; image matching; image retrieval; probability; vocabulary; Corel5k image; automatic image annotation; computer vision; feature extraction; generative model calculation; image retrieval; image similarity; semantic information; vocabulary prior probability; Accuracy; Computational modeling; Image recognition; Image segmentation; Oceans; Probability; Snow; Generative model; Image annotation; Image retrieval; Vocabulary prior probability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
Type :
conf
DOI :
10.1109/ICICISYS.2010.5658263
Filename :
5658263
Link To Document :
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