Query difficulty guided image retrieval system

Authors:
Yangxi Li;Yong Luo;Dacheng Tao;Chao Xu
Affiliations:
Key Laboratory of Machine Perception, Peking University, Beijing;Key Laboratory of Machine Perception, Peking University, Beijing;School of Computer Engineering, Nanyang Technological University, Singapore;Key Laboratory of Machine Perception, Peking University, Beijing
Venue:
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part II
Year:
2011

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Abstract

Query difficulty estimation is a useful tool for content-based image retrieval. It predicts the performance of the search result of a given query, and thus it can guide the pseudo relevance feedback to rerank the image search results, and can be used to re-write the given query by suggesting "easy" alternatives. This paper presents a query difficulty estimation guided image retrieval system. The system initially estimates the difficulty of a given query image by analyzing both the query image and the retrieved top ranked images. Different search strategies are correspondingly applied to improve the retrieval performance.