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Multi-camera Matching under Illumination Change Over Time

Abstract : Illumination differences between disjoint cameras can have a dramatic effect on the appearance of objects, thus increasing the difficulty of multi-camera object association. Although methods to model these inter-camera illumination conditions exist, they often rely on static illumination conditions and are unable to cope with unpredictable illumination changes over time. In this paper we propose a novel method for multi-camera object association based on adapting a learned inter-camera illumination mapping function to new illumination conditions over time without the need for a manual training stage using new foreground objects. Comparative experiments are carried out using challenging data taken from a disjoint camera network. The results demonstrate that the proposed method outperforms a number of existing methods given changing illumination conditions.
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https://hal.inria.fr/inria-00326772
Contributor : Peter Sturm <>
Submitted on : Sunday, October 5, 2008 - 2:45:30 PM
Last modification on : Monday, October 6, 2008 - 9:23:06 AM
Long-term archiving on: : Monday, October 8, 2012 - 2:00:15 PM

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  • HAL Id : inria-00326772, version 1

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Bryan Prosser, Shaogang Gong, Tao Xiang. Multi-camera Matching under Illumination Change Over Time. Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications - M2SFA2 2008, Andrea Cavallaro and Hamid Aghajan, Oct 2008, Marseille, France. ⟨inria-00326772⟩

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