Binary SIFT: Fast image retrieval using binary quantized SIFT features

Proceedings - International Workshop on Content-Based Multimedia Indexing

Volumn , Issue , 2011, Pages 217-222

  Peker, Kadir A ^a  

^a MELIKSAH UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

BINARY PATTERNS; BINARY VECTORS; CHEMICAL DATABASE; CONTENT BASED IMAGE RETRIEVAL; CURRENT PERFORMANCE; DISTANCE COMPUTATION; INDEXING TECHNIQUES; KEYPOINTS; MATCHING PROPERTY; MEDIAN VALUE; SHOW THROUGH; SIFT FEATURE; SQUARE OPERATIONS; TEST SETS;

IMAGE MATCHING; INDEXING (OF INFORMATION); VECTOR SPACES; VECTORS;

IMAGE RETRIEVAL;

EID: 80052275017     PISSN: 19493991     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CBMI.2011.5972548     Document Type: Conference Paper

References (6)

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2. RitendraDatta, Dhiraj Joshi, Jia Li and James Z. Wang, "Image Retrieval: Ideas, Influences, and Trends of the New Age," ACM Computing Surveys, vol. 40, no. 2, article 5, pp. 1-60, 2008.
3. Mikolajczyk, K. and Schmid, C. "Scale and affine invariant interest point detectors", Intl. J. Comput. Vision 60, 1, 63-86, 2004.
4. Lowe, D. "Distinctive Image Features from Scale-Invariant Keypoints", Intnl. Journal of Computer Vision 60(2):91-110, 2004.
5. K. Grauman and T. Darrell, "Efficient Image Matching with Distributions of Local Invariant Features", IEEE CVPR, San Diego, CA, June 2005.
6. Crandall, D. J., Backstrom, L., Huttenlocher, D., and Kleinberg, J. "Mapping the world's photos," In WWW '09: Proceedings of the 18th international conference on World wide web, pages 761-770, New York, NY, USA. ACM.(2009).