venkatesh-pedestriandetection-2008.pdf (1.18 MB)
Pedestrian detection for mobile bus surveillance
conference contribution
posted on 2008-01-01, 00:00 authored by W Leoputra, Svetha VenkateshSvetha Venkatesh, T TanIn 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.
History
Event
International Conference on Control, Automation, Robotics and Vision (10th : 2008 : Hanoi, Vietnam)Pagination
726 - 732Publisher
IEEELocation
Hanoi, VietnamPlace of publication
[Washington, D. C.]Start date
2008-12-17End date
2008-12-20ISBN-13
9781424422869ISBN-10
1424422868Language
engNotes
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.Publication classification
E1.1 Full written paper - refereedCopyright notice
2008, IEEETitle of proceedings
ICARCV 2008 : Proceedings of the 10th International Conference on Control, Automation, Robotics and VisionUsage metrics
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