Efficient target search with relevance feedback for large CBIR systems

Proceedings of the ACM Symposium on Applied Computing

Volumn 2, Issue , 2006, Pages 1393-1397

  Liu, Danzhou ^a   Hua, Kien A ^a   Vu, Khanh ^a   Yu, Ning ^a  

^a UNIVERSITY OF CENTRAL FLORIDA   (United States)

Author keywords

Image retrieval; Query point movement; Relevance feedback; Target search

Indexed keywords

COMPUTATIONAL COMPLEXITY; COMPUTER SIMULATION; INPUT OUTPUT PROGRAMS; PROBLEM SOLVING; QUERY LANGUAGES;

QUERY POINT MOVEMENT; RELEVANCE FEEDBACK; TARGET SEARCH;

CONTENT BASED RETRIEVAL;

EID: 33751062654     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1141277.1141598     Document Type: Conference Paper

References (8)

1. K. Chakrabarti, O.-B. Michael, S. Mehrotra, and K. Porkaew. Evaluating refined queries in top-k retrieval systems. IEEE Transactions on Knowledge and Data Engineering, 16(2):256-270, 2004.
2. I. J. Cox, M. L. Miller, T. P. Minka, T. V. Papathomas, and P. N. Yianilos. The Bayesian image retrieval system, PicHunter: theory, implementation, and psychophysical experiments. IEEE Transactions on Image Processing, 9(1):20-37, 2000.
3. M. Flickner, H. S. Sawhney, J. Ashley, Q. Huang, B. Dom, M. Gorkani, J. Hafher, D. Lee, D. Petkovic, D. Steele, and P. Yanker. Query by image and video content: The QBIC system. IEEE Computer, 28(9):23-32, 1995.
4. T. Gevers and A. Smeulders. Content-based image retrieval: An overview. In G. Medioni and S. B. Kang, editors, Emerging Topics in Computer Vision. Prentice Hall, 2004.
5. K. A. Hua, N. Yu, and D. Liu. Query Decomposition: a multiple neighborhood approach to relevance feedback processing in content-based image retrievall. In Proceedings of the 22nd International Conference on Data Engineering, 2006.
6. Y. Ishikawa, R. Subramanya, and C. Faloutsos. MindReader: Querying databases through multiple examples. In Proceedings of the 24th VLDB Conference, pages 218-227, 1998.
7. D.-H. Kim and C.-W. Chung. Qcluster: relevance feedback using adaptive clustering for content-based image retrieval. In Proceedings of the A CM SIGMOD Conference, pages 599-610, 2003.
8. O.-B. Michael and S. Mehrotra. Relevance feedback techniques in the MARS image retrieval systems. Multimedia Systems, (9):535-547, 2004.