By Topic

Simultaneous inference of activity, pose and object

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Khan, F.M. ; Inst. of Robot. & Intell. Syst., Univ. of Southern California, Los Angeles, CA, USA ; Singh, V.K. ; Nevatia, R.

Human movements are important cues for recognizing human actions, which can be captured by explicit modeling and tracking of actor or through space-time low-level features. However, relying solely on human dynamics is not enough to discriminate between actions which have similar human dynamics, such as smoking and drinking, irrespective of the modeling method. Object perception plays an important role in such cases. Conversely, human movements are indicative of type of object used for the action. These two processes of object perception and action understanding are thus not independent. Consequently, action recognition improves when human movements and object perception are used in conjunction. Therefore, we propose a probabilistic approach to simultaneously infer what action was performed, what object was used and what poses the actor went through. This joint inference framework can better discriminate between actions and objects which are too similar and lack discriminative features.

Published in:

Applications of Computer Vision (WACV), 2012 IEEE Workshop on

Date of Conference:

9-11 Jan. 2012