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.
Type de document :
Communication dans un congrès
Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications - M2SFA2 2008, Oct 2008, Marseille, France. 2008
Liste complète des métadonnées

https://hal.inria.fr/inria-00326772
Contributeur : Peter Sturm <>
Soumis le : dimanche 5 octobre 2008 - 14:45:30
Dernière modification le : lundi 6 octobre 2008 - 09:23:06
Document(s) archivé(s) le : lundi 8 octobre 2012 - 14:00:15

Fichier

1569139896.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : inria-00326772, version 1

Collections

Citation

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, Oct 2008, Marseille, France. 2008. 〈inria-00326772〉

Partager

Métriques

Consultations de la notice

340

Téléchargements de fichiers

254