Openly accessible

Passenger monitoring in moving bus video

Leoputra, Wilson S., Venkatesh, Svetha and Tan, Tele 2008, Passenger monitoring in moving bus video, in ICARCV 2008 : Proceedings of the 10th International Conference on Control, Automation, Robotics and Vision, IEEE, [Washington, D. C.], pp. 719-725.

Attached Files
Name Description MIMEType Size Downloads
venkatesh-passengermonitoring-2008.pdf Published version application/pdf 1.44MB 61

Title Passenger monitoring in moving bus video
Author(s) Leoputra, Wilson S.
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Tan, Tele
Conference name International Conference on Control, Automation, Robotics and Vision (10th : 2008 : Hanoi, Vietnam)
Conference location Hanoi, Vietnam
Conference dates 17-20 Dec. 2008
Title of proceedings ICARCV 2008 : Proceedings of the 10th International Conference on Control, Automation, Robotics and Vision
Editor(s) [Unknown]
Publication date 2008
Conference series International Conference on Control, Automation, Robotics and Vision
Start page 719
End page 725
Total pages 7
Publisher IEEE
Place of publication [Washington, D. C.]
Keyword(s) bayesian inference
elliptical human detection
homography
SIFT background model
Summary In this paper, we present a novel person detection system for public transport buses tackling the problem of changing illumination conditions. Our approach integrates a stable SIFT (Scale Invariant Feature Transform) background seat modeling mechanism with a human shape model into a weighted Bayesian framework to detect passengers on-board buses. SIFT background modeling extracts local stable features on the pre-annotated background seat areas and tracks these features over time to build a global statistical background model for each seat. Since SIFT features are partially invariant to lighting, this background model can be used robustly to detect the seat occupancy status even under severe lighting changes. The human shape model further confirms the existence of a passenger when a seat is occupied. This constructs a robust passenger monitoring system which is resilient to illumination changes. We evaluate the performance of our proposed system on a number of challenging video datasets obtained from bus cameras and the experimental results show that it is superior to state-of-art people detection systems.
Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
ISBN 1424422868
9781424422869
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2008, IEEE
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044573

Document type: Conference Paper
Collections: School of Information Technology
Open Access Collection
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 1 times in TR Web of Science
Scopus Citation Count Cited 3 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 339 Abstract Views, 61 File Downloads  -  Detailed Statistics
Created: Fri, 20 Apr 2012, 11:33:06 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.