By Topic

Perspective and appearance context for people surveillance in open areas

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

3 Author(s)
Giovanni Gualdi ; D.I.I. Univ. of Modena and Reggio Emilia, Italy ; Andrea Prati ; Rita Cucchiara

Contextual information can be used both to reduce computations and to increase accuracy and this paper presents how it can be exploited for people surveillance in terms of perspective (i.e. weak scene calibration) and appearance of the objects of interest (i.e. relevance feedback on the training of a classifier). These techniques are applied to a pedestrian detector that exploits covariance descriptors through a LogitBoost classifier on Riemannian manifolds. The approach has been tested on a construction working site where complexity and dynamics are very high, making human detection a real challenge. The experimental results demonstrate the improvements achieved by the proposed approach.

Published in:

2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops

Date of Conference:

13-18 June 2010