A Fast Audiovisual Attention Model for Human Detection and Localization on a Companion Robot

Abstract : This paper describes a fast audiovisual attention model applied to human detection and localization on a companion robot. Its originality lies in combining static and dynamic modalities over two analysis paths in order to guide the robot's gaze towards the most probable human beings' locations based on the concept of saliency. Visual, depth and audio data are acquired using a RGB-D camera and two horizontal microphones. Adapted state-of-the-art methods are used to extract relevant information and fuse them together via two dimensional gaussian representations. The obtained saliency map represents human positions as the most salient areas. Experiments have shown that the proposed model can provide a mean F-measure of 66 percent with a mean precision of 77 percent for human localization using bounding box areas on 10 manually annotated videos. The corresponding algorithm is able to process 70 frames per second on the robot.
Type de document :
Communication dans un congrès
The First International Conference on Applications and Systems of Visual Paradigms (VISUAL 2016), Nov 2016, Barcelone, Spain. VISUAL 2016 Proceedings - ThinkMind
Liste complète des métadonnées


https://hal.archives-ouvertes.fr/hal-01408740
Contributeur : Denis Pellerin <>
Soumis le : lundi 5 décembre 2016 - 12:33:18
Dernière modification le : vendredi 9 juin 2017 - 01:08:14
Document(s) archivé(s) le : lundi 20 mars 2017 - 16:48:07

Fichier

16_Visual_ratajczak_.pdf
Fichiers produits par l'(les) auteur(s)

Licence


Copyright (Tous droits réservés)

Identifiants

  • HAL Id : hal-01408740, version 1

Citation

Rémi Ratajczak, Denis Pellerin, Quentin Labourey, Catherine Garbay. A Fast Audiovisual Attention Model for Human Detection and Localization on a Companion Robot. The First International Conference on Applications and Systems of Visual Paradigms (VISUAL 2016), Nov 2016, Barcelone, Spain. VISUAL 2016 Proceedings - ThinkMind. <hal-01408740>

Partager

Métriques

Consultations de
la notice

326

Téléchargements du document

110