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Pedestrian detection for mobile bus surveillance

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conference contribution
posted on 2008-01-01, 00:00 authored by W Leoputra, Svetha VenkateshSvetha Venkatesh, T Tan
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.

History

Event

International Conference on Control, Automation, Robotics and Vision (10th : 2008 : Hanoi, Vietnam)

Pagination

726 - 732

Publisher

IEEE

Location

Hanoi, Vietnam

Place of publication

[Washington, D. C.]

Start date

2008-12-17

End date

2008-12-20

ISBN-13

9781424422869

ISBN-10

1424422868

Language

eng

Notes

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Publication classification

E1.1 Full written paper - refereed

Copyright notice

2008, IEEE

Title of proceedings

ICARCV 2008 : Proceedings of the 10th International Conference on Control, Automation, Robotics and Vision