By Topic

Action recognition in intelligent environments using point cloud features extracted from silhouette sequences

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

5 Author(s)
Rusu, R.B. ; Intell. Autonomous Syst., Tech. Univ. Munchen, Munich ; Bandouch, J. ; Marton, Z.C. ; Blodow, N.
more authors

In this paper we present our work on human action recognition in intelligent environments. We classify actions by looking at a time-sequence of silhouettes extracted from various camera images. By treating time as the third spatial dimension we generate so-called space-time shapes that contain rich information about the actions. We propose a novel approach for recognizing actions, by representing the shapes as 3D point clouds and estimating feature histograms for them. Preliminary results show that our method robustly derives different classes of actions, even in the presence of large variability in the data, coming from different persons at different time intervals.

Published in:

Robot and Human Interactive Communication, 2008. RO-MAN 2008. The 17th IEEE International Symposium on

Date of Conference:

1-3 Aug. 2008