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Latest revision as of 17:42, 28 January 2021
Abstract
The automatic detection and tracking of pedestrians in imagery constitute important and challenging problems both in computer vision and driver assistance systems. We address these problems for the case of a forward looking monocular infrared camera under strong vehicle induced camera motion. An integrated detection & tracking strategy is introduced based on a state-of-the-art feature based object detector originally developed for images in the visual spectrum. The proposed pedestrian detection algorithm can be applied to both infrared and visual imagery. We show the difficulties arising from the specifics of infrared data under strong camera motion and how to tackle these problems by replacing common motion models like the Kalman filter by a feature matching approach.
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Published on 01/01/2010
Volume 2010, 2010
DOI: 10.1109/ivs.2010.5548132
Licence: CC BY-NC-SA license
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