LobNet platform: Target tracking with a low resolution camera network

Abstract : In this paper, we present a new platform for environment monitoring using very low specification cameras. These latter are distinguished by their visual sensors offering tiny images (30*30 pixels), completely local processing thanks to the max10 FPGA and the SmartMesh IP technology offering a mesh network. The lack of information extracted by visual sensors is filled by intensive communication and data exchanged between cameras after each detection. Thus, a re-identification process is applied based on exchanged and extracted data after each target detection.
Type de document :
Communication dans un congrès
Unconventional Sensing and Processing for Robotic Visual Perception workshop, IEEE/RSJ International Conference on Intelligent Robots and Systems, Oct 2018, Madrid, Spain. 〈http://iros2018-uvsp.org/〉
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01966756
Contributeur : Jean-Charles Quinton <>
Soumis le : samedi 29 décembre 2018 - 16:02:43
Dernière modification le : jeudi 17 janvier 2019 - 15:17:05

Fichier

Lobna - IROS2018 workshop - ie...
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01966756, version 1

Citation

Lobna Khelifa, François Berry, Jean-Charles Quinton. LobNet platform: Target tracking with a low resolution camera network. Unconventional Sensing and Processing for Robotic Visual Perception workshop, IEEE/RSJ International Conference on Intelligent Robots and Systems, Oct 2018, Madrid, Spain. 〈http://iros2018-uvsp.org/〉. 〈hal-01966756〉

Partager

Métriques

Consultations de la notice

13

Téléchargements de fichiers

7