Pedestrian detection for mobile bus surveillance Leoputra, Wilson S., Venkatesh, Svetha and Tan, Tele 2008, Pedestrian detection for mobile bus surveillance, in ICARCV 2008 : Proceedings of the 10th International Conference on Control, Automation, Robotics and Vision, IEEE, [Washington, D. C.], pp. 726-732. Attached Files Name Description MIMEType Size Downloads venkatesh-pedestriandetection-2008.pdf Published version application/pdf 1.17MB 71 Title Pedestrian detection for mobile bus surveillance Author(s) Leoputra, Wilson S. 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 726 End page 732 Total pages 7 Publisher IEEE Place of publication [Washington, D. C.] Keyword(s) hierarchical template matching homography non-parametric background modeling scene localization Summary In this paper, we present a system for pedestrian detection involving scenes captured by mobile bus surveillance cameras in busy city streets. Our approach integrates scene localization, foreground and background separation, and pedestrian detection modules into a unified detection framework. The scene localization module performs a two stage clustering of the video data. In the first stage, SIFT Homography is applied to cluster frames in terms of their structural similarities and second stage further clusters these aligned frames in terms of lighting. This produces clusters of images which are differential in viewpoint and lighting. A kernel density estimation (KDE) method for colour and gradient foreground-background separation are then used to construct background model for each image cluster which is subsequently used to detect all foreground pixels. Finally, using a hierarchical template matching approach, pedestrians can be identified. We have tested our system on a set of real bus video datasets and the experimental results verify that our system works well in practice. 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:30044574 Document type: Conference Paper Collections: School of Information Technology Open Access Collection Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     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 Fri, 20 Apr 2012, 11:33:09 EST Thu, 26 Apr 2012, 16:48:39 EST Thu, 26 Apr 2012, 16:57:31 EST Mon, 30 Apr 2012, 08:44:02 EST Tue, 01 May 2012, 15:52:54 EST Mon, 04 Aug 2014, 12:39:02 EST Tue, 06 Sep 2016, 18:43:36 EST Sat, 21 Oct 2017, 02:03:11 EST Tue, 05 Dec 2017, 12:31:22 EST Filtered Full Citation counts:   Cited 1 times in TR Web of Science Cited 4 times in Scopus Search Google Scholar Access Statistics: 300 Abstract Views, 68 File Downloads  -  Detailed Statistics Created: Fri, 20 Apr 2012, 11:33:09 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.