Learning to Rerank Web Images

This article reviews recent advancements in developing approaches to Web image search reranking. The authors provide a categorization of related theories and algorithms and include a mathematical formulation, analysis, and discussion per category. They highlight the limitations of the existing approaches and make recommendations on what they believe to be the most critical research directions to improve the efficiency, effectiveness, and overall utility of Web image search reranking technology.

[1]  Shih-Fu Chang,et al.  Video search reranking via information bottleneck principle , 2006, MM '06.

[2]  Andrew Zisserman,et al.  Image Classification using Random Forests and Ferns , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[3]  Shih-Fu Chang,et al.  Reranking Methods for Visual Search , 2007, IEEE MultiMedia.

[4]  Alan Hanjalic,et al.  Learning from search engine and human supervision for web image search , 2011, MM '11.

[5]  Thorsten Joachims,et al.  Optimizing search engines using clickthrough data , 2002, KDD.

[6]  Stevan Rudinac,et al.  Exploiting noisy visual concept detection to improve spoken content based video retrieval , 2010, ACM Multimedia.

[7]  Shih-Fu Chang,et al.  Video search reranking through random walk over document-level context graph , 2007, ACM Multimedia.

[8]  Frédéric Jurie,et al.  Improving web image search results using query-relative classifiers , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  Xian-Sheng Hua,et al.  Bayesian video search reranking , 2008, ACM Multimedia.

[10]  Vidit Jain,et al.  Learning to re-rank: query-dependent image re-ranking using click data , 2011, WWW.

[11]  Ximena Olivares,et al.  Visual diversification of image search results , 2009, WWW '09.

[12]  Rong Yan,et al.  Multimedia Search with Pseudo-relevance Feedback , 2003, CIVR.

[13]  Antonio Torralba,et al.  Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope , 2001, International Journal of Computer Vision.

[14]  Alan Hanjalic,et al.  Supervised reranking for web image search , 2010, ACM Multimedia.

[15]  Shumeet Baluja,et al.  VisualRank: Applying PageRank to Large-Scale Image Search , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  Tie-Yan Liu,et al.  Learning to Rank for Information Retrieval , 2011 .

[17]  Qi Tian,et al.  Learning to judge image search results , 2011, MM '11.