EagleRank: a novel ranking model for web image search engine
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
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Abstract: In recent years, image retrieval has received tremendous attentions and some progresses have been made. However, most existing work on image retrieval focuses on specific issues and techniques local to image computing or access. Little work has been done to combine various aspects into a single framework. In this paper, we describe our approach of developing a general-purpose image retrieval system over the web. A main feature of our system is its hybrid approach by integrating both semantic and visual feature retrieval methods. By combining keyword-based query selection with content-based retrieval techniques, the system is able to provide effective image searching and retrieval. The results are further improved through a relevance feedback process. A research prototype system has been constructed on a web environment, and experimental results demonstrate the effectiveness of the new approach.