Video-based image retrieval

MM'11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops

Volumn , Issue , 2011, Pages 1001-1004

  Yang, Linjun ^a   Cai, Yang ^b   Hanjalic, Alan ^c   Hua, Xian Sheng ^d   Li, Shipeng ^a  

^a MICROSOFT RESEARCH ASIA   (China)

^b ZHEJIANG UNIVERSITY   (China)

^c DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

^d MICROSOFT   (United States)

Author keywords

Content based image retrieval; Video based image retrieval

Indexed keywords

CONTENT BASED IMAGE RETRIEVAL; IMAGE RETRIEVAL SYSTEMS; QUERY IMAGES; QUERY-BY-EXAMPLE; SINGLE IMAGES; VIDEO CLIPS; VIDEO FRAME;

SEARCH ENGINES;

IMAGE RETRIEVAL;

EID: 84355167603     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2072298.2071923     Document Type: Conference Paper

References (8)

1. http://www.robots.ox.ac.uk/~vgg/data/oxbuildings.
2. G. Bradski and A. Kaehler. Learning OpenCV: Computer Vision with the OpenCV Library. O'Reilly, Cambridge, MA, 2008.
3. D. Li, L. Yang, X.-S. Hua, and H.-J. Zhang. Large-scale robust visual codebook construction. In ACM Multimedia, 2010.
4. D. G. Lowe. Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision, 60(2):91-110, 2004.
5. B. D. Lucas and T. Kanade. An Iterative Image Registration Technique with an Application to Stereo Vision. In Proc. of the 1981 DARPA Imaging Understanding Workshop, 1981.
6. J. Sivic, F. Schaffalitzky, and A. Zisserman. Object level grouping for video shots. 2004.
7. J. Sivic and A. Zisserman. Video google: A text retrieval approach to object matching in videos. In ICCV, 2003.
8. D. Stavens and S. Thrun. Unsupervised learning of invariant features using video. In CVPR, 2010.