CUHK at ImageCLEF 2005: Cross-Language and Cross-Media Image Retrieval

  • Steven C. H. Hoi
  • Jianke Zhu
  • Michael R. Lyu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4022)


In this paper, we describe our studies of cross-language and cross-media image retrieval at the ImageCLEF 2005. This is the first participation of our CUHK (The Chinese University of Hong Kong) group at ImageCLEF. The task in which we participated is the “bilingual ad hoc retrieval” task. There are three major focuses and contributions in our participation. The first is the empirical evaluation of language models and smoothing strategies for cross-language image retrieval. The second is the evaluation of cross-media image retrieval, i.e., combining text and visual contents for image retrieval. The last is the evaluation of bilingual image retrieval between English and Chinese. We provide an empirical analysis of our experimental results, in which our approach achieves the best mean average precision result in the monolingual query task in the campaign. Finally we summarize our empirical experience and address the future improvement of our work.


Discrete Cosine Transform Image Retrieval Visual Content Retrieval Task Query Translation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Steven C. H. Hoi
    • 1
  • Jianke Zhu
    • 1
  • Michael R. Lyu
    • 1
  1. 1.Department of Computer Science and EngineeringThe Chinese University of Hong KongShatin, N.T., Hong Kong

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