Towards Reliable Real-Time Person Detection

Abstract : We propose a robust real-time person detection system, which aims to serve as solid foundation for developing solutions at an elevated level of reliability. Our belief is that clever handling of input data correlated with efficacious training algorithms are key for obtaining top performance. We introduce a comprehensive training method based on random sampling that compiles optimal classifiers with minimal bias and overfit rate. Building upon recent advances in multi-scale feature computations, our approach attains state-of-the-art accuracy while running at high frame rate.
Type de document :
Communication dans un congrès
VISAPP - The International Conference on Computer Vision Theory and Applications, Jan 2014, Lisbon, Portugal. 2014
Liste complète des métadonnées

Littérature citée [37 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-00909124
Contributeur : Silviu-Tudor Serban <>
Soumis le : lundi 25 novembre 2013 - 18:30:24
Dernière modification le : jeudi 11 janvier 2018 - 16:39:59
Document(s) archivé(s) le : mercredi 26 février 2014 - 09:55:17

Fichier

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

Identifiants

  • HAL Id : hal-00909124, version 1

Collections

Citation

Silviu-Tudor Serban, Srinidhi Mukanahallipatna Simha, Vasanth Bathrinarayanan, Etienne Corvee, Francois Bremond. Towards Reliable Real-Time Person Detection. VISAPP - The International Conference on Computer Vision Theory and Applications, Jan 2014, Lisbon, Portugal. 2014. 〈hal-00909124〉

Partager

Métriques

Consultations de la notice

329

Téléchargements de fichiers

635