Tuesday 21st of November 2017
 

Automatic Image Annotation Using Modified Keywords Transfer Mechanism Base on Image-Keyword Graph


, Guo-Qing Xu, and Zhi-Chun Mu

Automatic image annotation is widely considered to be an important yet open problem due to the well-known semantic gap. Recent works show that nearest-neighbor-based annotation approaches are simple and effective. In this paper we use a modified keywords transfer mechanism base on image-keyword unidirectional graph to derive a great annotator. The unidirectional graph describes the relationships between images and keywords, and can be derived from images with human annotations. On that basis, a modified keywords transfer mechanism base on visual neighbors is used to annotate new images. Our method achieves better annotation performance than two of the most advanced annotation methods in terms of precision, recall and F1 metrics on the open benchmark database.

Keywords: Automatic Image Annotation, Semantic Gap, Keywords Transfer, Graph, Visual Neighbors.

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ABOUT THE AUTHORS




Guo-Qing Xu
He received the B.E. degree from the School of Electrical Engineering at Zhengzhou University in 2008. He is currently pursuing Ph.D. in Control Science and Control Engineering from the School of Automation and Electrical Engineering, University of Science and Technology Beijing. His research interests include content-based image retrieval, automatic image annotation, machine learning, and pattern recognition.




Zhi-Chun Mu
He received the B.E. and M.E. degrees from the Department of Automation at University of Science and Technology Beijing in 1978 and 1983, respectively. He is currently a professor in the School of Automation and Electrical Engineering, University of Science and Technology Beijing. He was a visiting scholar at Davy International UK and Sheffield Polytechnic, England, from 1989 to 1991, and a visiting Professor at University of Brighton, England from 1996 to 1999. As a Guest Professor, he visited Laboratoire d¡¯Electronique, d¡¯Informatique et d¡¯Image, CNRS University of Burgundy France in 2007. He was the Chair of Organizing Committee of IEEE International Conference on Wavelet Analysis and Pattern Recognition 2007. He has served as a reviewer and member of Evaluation and Assessment Commission, Division of Information Science, National Natural Science Foundation of China since 2002.He is now Chair of IEEE SMC Beijing (capital region) Chapter. His main research interests include Pattern Recognition and Biometrics, Artificial Intelligence and its applications, Data Mining as well as Process Control and Modeling. He has published more than 180 refereed journal and conference papers in these areas. He is the corresponding author of this paper.


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