By Topic

One video is sufficient? Human activity recognition using active video composition

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
$33 $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

2 Author(s)
M. S. Ryoo ; Electronics and Telecommunications Research Institute, Daejeon, Korea ; Wonpil Yu

In this paper, we present a novel human activity recognition approach that only requires a single video example per activity. We introduce the paradigm of active video composition, which enables one-example recognition of complex activities. The idea is to automatically create a large number of semi-artificial training videos called composed videos by manipulating an original human activity video. A methodology to automatically compose activity videos having different backgrounds, translations, scales, actors, and movement structures is described in this paper. Furthermore, an active learning algorithm to model the temporal structure of the human activity has been designed, preventing the generation of composed training videos violating the structural constraints of the activity. The intention is to generate composed videos having correct organizations, and take advantage of them for the training of the recognition system. In contrast to previous passive recognition systems relying only on given training videos, our methodology actively composes necessary training videos that the system is expected to observe in its environment. Experimental results illustrate that a single fully labeled video per activity is sufficient for our methodology to reliably recognize human activities by utilizing composed training videos.

Published in:

Applications of Computer Vision (WACV), 2011 IEEE Workshop on

Date of Conference:

5-7 Jan. 2011