Object Detection and Matching with Mobile Cameras Collaborating with Fixed Cameras

Alexandre Alahi 1, 2 Michel Bierlaire 2 Murat Kunt 1
1 SP Lab - Laboratoire de Traitement du signal [EPFL] / Signal Processing Laboratories
2 Transportation and Mobility Laboratory
Abstract : A system is presented to detect and match any objects with mobile cameras collaborating with fixed cameras observing the same scene. No training data is needed. Various object descriptors are studied based on grids of region descriptors. Region descriptors such as histograms of oriented gradients and covariance matrices of different set of features are evaluated. A detection and matching approach is presented based on a cascade of descriptors outperforming previous approaches. The object descriptor is robust to any changes in illuminations, viewpoints, color distributions and image quality. Objects with partial occlusion are also detected. The dynamic of the system is taken into consideration to better detect moving objects. Qualitative and quantitative results are presented in indoor and outdoor urban scenes.
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-00326759
Contributeur : Peter Sturm <>
Soumis le : dimanche 5 octobre 2008 - 14:05:45
Dernière modification le : lundi 2 octobre 2017 - 16:06:02
Document(s) archivé(s) le : lundi 8 octobre 2012 - 13:57:51

Fichier

1569139998.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : inria-00326759, version 1

Collections

M2SFA2

Citation

Alexandre Alahi, Michel Bierlaire, Murat Kunt. Object Detection and Matching with Mobile Cameras Collaborating with Fixed Cameras. Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications - M2SFA2 2008, Oct 2008, Marseille, France. 2008. 〈inria-00326759〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

222

Téléchargements de fichiers

73

Contact


archive-ouverte@inria.fr