Image Annotation Based on Graph Learning
Lu Han · Chinese Journal of Computers · 2008
Image annotation is an important and challenging task in image retrieval.This paper discusses the annotation process theoretically by reviewing some related work,and proposes a unified annotation framework via graph learning.The framework includes two sub-processes,i.e.,basic image annotation and annotation refinement.In the basic annotation process,the image-based graph learning is utilized to obtain the candidate annotations.In the annotation refinement process,the word-based graph learning is used to refine those candidate annotations from the prior process.This paper also proposes some improvements on sub-problems involved in the framework and expect their combination to enhance the overall performance.Finally,experiments conducted on the Corel dataset and Web image dataset demonstrate the effectiveness of the unified framework and the proposed improvements.