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Real time google and live image search re-ranking

Published: 26 October 2008 Publication History

Abstract

Nowadays, web-scale image search engines (e.g. Google, Live Image Search) rely almost purely on surrounding text features. This leads to ambiguous and noisy results. We propose to use adaptive visual similarity to re-rank the text-based search results. A query image is first categorized into one of several predefined intention categories, and a specific similarity measure is used inside each category to combine image features for re-ranking based on the query image. Extensive experiments demonstrate that using this algorithm to filter output of Google and Live Image Search is a practical and effective way to dramatically improve the user experience. A real-time image search engine is developed for on-line image search with re-ranking: http://mmlab.ie.cuhk.edu.hk/intentsearch

References

[1]
Google Image Search. http://images.google.com.
[2]
http://www.live.com/~&scope=images.
[3]
J. Cui, F. Wen, and X. Tang. Intentsearch: Interactive on-line image search re-ranking. In MULTIMEDIA '08: Proceedings of the 16th international conference on Multimedia, 2008.
[4]
N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In CVPR, 2005.
[5]
R. Fergus, L. Fei-Fei, P. Perona, and A. Zisserman. Learning object categories from google's image search. In ICCV, 2005.
[6]
R. Fergus, P. Perona, and A. Zisserman. A visual category filter for google images. In ECCV, 2004.
[7]
W. Freeman and M. Roth. Orientation histogram for hand gesture recognition. In Int'l Workshop on Automatic Face- and Gesture-Recognition, 1995.
[8]
Y. Freund, R. Iyer, R. E. Schapire, and Y. Singer. An efficient boosting algorithm for combining preferences. J. Mach. Learn. Res., 4:933--969, 2003.
[9]
W. H. Hsu, L. S. Kennedy, and S.-F. Chang. Novel reranking methods for visual search. IEEE Multimedia, 2007.
[10]
T. Liu, J. Sun, N.-N. Zheng, X. Tang, and H.-Y. Shum. Learning to detect a salient object. In CVPR, 2007.
[11]
D. G. Lowe. Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision, 60(2):91--110, 2004.
[12]
Y. Luo and X. Tang. Photo and video quality evaluation: Focusing on the subject. In MULTIMEDIA '08: Proceedings of the 16th international conference on Multimedia, 2008.
[13]
J. R. Quinlan. C4.5: programs for machine learning. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 1993.
[14]
Y. Rubner, L. J. Guibas, and C. Tomasi. The earth mover's distance, multi-dimensional scaling, and color-based image retrieval. In Proceedings of the ARPA Image Understanding Workshop, 1997.
[15]
A. Torralba, K. Murphy, W. Freeman, and M. Rubin. Context-based vision system for place and object recognition, 2003.
[16]
M. Unser. Texture classification and segmentation using wavelet frames. IEEE TIP, 4:1549--1560, 1995.
[17]
R. Xiao, H. Zhu, H. Sun, and X. Tang. Dynamic cascades for face detection. In ICCV, 2007.
[18]
X. S. Zhou and T. S. Huang. Relevance feedback in image retrieval: A comprehensive review. Multimedia Systems, 8(6):536--544, 2003.

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cover image ACM Conferences
MM '08: Proceedings of the 16th ACM international conference on Multimedia
October 2008
1206 pages
ISBN:9781605583037
DOI:10.1145/1459359
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 26 October 2008

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Author Tags

  1. adaptive similarity
  2. image search
  3. intention
  4. visual

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MM08
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MM08: ACM Multimedia Conference 2008
October 26 - 31, 2008
British Columbia, Vancouver, Canada

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