A semantic-guided and self-configurable framework for video analysis-Reference-Cited by-同舟云学术

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A semantic-guided and self-configurable framework for video analysis

Published:2011-12-14 Issue:3 Volume:24 Page:493-512
ISSN:0932-8092
Container-title:Machine Vision and Applications
language:en
Short-container-title:Machine Vision and Applications

Author:

SanMiguel Juan C.,Martínez José M.

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

http://link.springer.com/content/pdf/10.1007/s00138-011-0397-x.pdf

Reference41 articles.

1. Apt K.R.: Principles of Constraint Programming. Cambridge University Press, Cambridge (2003)

2. Avanzi A., Bremond F., Tornieri C., Thonnat M.: Design and assessment of an intelligent activity monitoring platform. EURASIP J. Appl. Signal Process 2005(14), 2359–2374 (2005)

3. Bai, L., Lao, S., Jones, G., Smeaton, A.: Video semantic content analysis based on ontology. In: Proceedings of International Machine Vision and Image Processing Conference, pp. 117–124. Maynooth (2007)

4. Bayona, A., San Miguel, J., Martinez, J.: Comparative evaluation of stationary foreground object detection algorithms based on background subtraction techniques. In: Proceedings of IEEE International Conference on Advanced Video and Signal based Surveillance, pp. 25–30. Genoa (2009)

5. Bayona, A., San Miguel, J., Martinez, J.: Stationary foreground detection using background subtraction and temporal difference in video surveillance. In: Proceedings of IEEE International Conference on Image Processing, pp. 4657–4660. Hong Kong (2010)

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