Learning Actions From the Web
Date
2010-07-06
DOI
Authors
Ikizler-Cinbis, Nazli
Cinbis, Gokberk
Sclaroff, Stan
Version
OA Version
Citation
Ikizler-Cinbis, Nazli; Cinbis, Gokberk; Sclaroff, Stan. "Learning Actions From the Web", Technical Report BUCS-TR-2010-017, Computer Science Department, Boston University, July 6, 2010. [Available from: http://hdl.handle.net/2144/3794]
Abstract
This paper proposes a generic method for action recognition in uncontrolled videos. The idea is to use images collected from the Web to learn representations of actions and use this knowledge to automatically annotate actions in videos. Our approach is unsupervised in the sense that it requires no human intervention other than the text querying. Its benefits are two-fold: 1) we can improve retrieval of action images, and 2) we can collect a large generic database of action poses, which can then be used in tagging videos. We present experimental evidence that using action images collected from the Web, annotating actions is possible.