Fast recursive ensemble convolution of haar-like features

Daniel Wesierski 1 Maher Mkhinini 1 Patrick Horain 1 Anna Jezierska 2
1 EPH - Département Electronique et Physique
2 LIGM - Laboratoire d'Informatique Gaspard-Monge
Abstract : Haar-like features are ubiquitous in computer vision, e.g. for Viola and Jones face detection or local descriptors such as Speeded-Up-Robust-Features. They are classically computed in one pass over integral image by reading the values at the feature corners. Here we present a new, general, parsing formalism for convolving them more efficiently. Our method is fully automatic and applicable to an arbitrary set of Haar-like features. The parser reduces the number of memory accesses which are the main computational bottleneck during convolution on modern computer architectures. It first splits the features into simpler kernels. Then it aligns and reuses them where applicable forming an ensemble of recursive convolution trees, which can be computed faster. This is illustrated with experiments, which show a significant speed-up over the classic approach.
Keywords : Computer architecture Convolution Face detection Feature extraction Kernel Vectors
Type de document :
Communication dans un congrès
CVPR "12 : IEEE Conference on Computer Vision and Pattern Recognition, Jun 2012, Providence, Rhode Island, United States. IEEE, pp.3689-3696, 2012, 〈10.1109/CVPR.2012.6248115〉
Liste complète des métadonnées

Littérature citée [17 références]  Voir  Masquer  Télécharger
https://hal.archives-ouvertes.fr/hal-00819740
Contributeur : Médiathèque Télécom Sudparis & Institut Mines-Télécom Business School <>
Soumis le : jeudi 2 mai 2013 - 10:55:37
Dernière modification le : mercredi 11 avril 2018 - 12:12:02
Document(s) archivé(s) le : lundi 19 août 2013 - 11:05:45

Fichier

Wesierski_2012_cvpr.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

TELECOM-SUDPARIS | PARISTECH | ENPC | UPEC-UPEM | UNIV-MLV | LIGM | LIGM_SIGNAL

Citation

Daniel Wesierski, Maher Mkhinini, Patrick Horain, Anna Jezierska. Fast recursive ensemble convolution of haar-like features. CVPR "12 : IEEE Conference on Computer Vision and Pattern Recognition, Jun 2012, Providence, Rhode Island, United States. IEEE, pp.3689-3696, 2012, 〈10.1109/CVPR.2012.6248115〉. 〈hal-00819740〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

249

Téléchargements de fichiers

107

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD