Search |  Contact |  SRI Home Do not follow this link, or your host will be blocked from this site. This is a spider trap. Do not follow this link, or your host will be blocked from this site. This is a spider trap. Do not follow this link, or your host will be blocked from this site. This is a spider trap.A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A ASRI International.  333 Ravenswood Avenue.  Menlo Park, CA 94025-3493. SRI International is a nonprofit corporation.

Publication in EndNote Format

%0 Conference Proceedings %A Connolly, C. I. %E Bebis, G. and Boyle, R. and Parvin, B. and Koracin, D. and Paragios, N. and Tanveer, S-M. and Ju, T. and Liu, Z. and Coquillart, S. and Cruz-Neira, C. and M\"{u}ller, T. and Malzbender, T. %T Learning to Recognize Complex Actions Using Conditional Random Fields %B Advances in Visual Computing %C Heidelberg %@ 978-3-540-76855-5 %I Springer %S Lecture Notes in Computer Science %P 340–348 %V 4842 %D 2007 %X Surveillance systems that operate continuously generate large volumes of data. One such system is described here, continuously tracking and storing observations taken from multiple stereo systems. Automated event recognition is one way of annotating track databases for faster search and retrieval. Recognition of complex events in such data sets often requires context for successful disambiguation of apparently similar activities. Conditional random fields permit straightforward incorporation of temporal context into the event recognition task. This paper describes experiments in activity learning, using conditional random fields to learn and recognize composite events that are captured by the observation stream. %O Proceedings of the 2007 International Symposium on Visual Computing %U http://www.ai.sri.com/pubs/files/1542.pdf

SRI International
©2014 SRI International 333 Ravenswood Avenue, Menlo Park, CA 94025-3493
SRI International is an independent, nonprofit corporation. Privacy policy