On Fisher vector encoding of binary features for video face recognition-Reference-Cited by-同舟云学术

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On Fisher vector encoding of binary features for video face recognition

Published:2018-02 Issue: Volume:51 Page:155-161
ISSN:1047-3203
Container-title:Journal of Visual Communication and Image Representation
language:en
Short-container-title:Journal of Visual Communication and Image Representation

Author:

Martínez-Díaz Yoanna,Hernández Noslen,Biscay Rolando J.,Chang Leonardo,Méndez-Vázquez Heydi,Enrique Sucar L.

Funder

FAPERJ/CAPES

FONCICYT

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Media Technology,Signal Processing

Reference40 articles.

1. Face recognition: challenges, achievements and future directions;Hassaballah;IET Comput. Vis.,2015

2. A review on state-of-the-art face recognition approaches;Mahmood;Fractals,2017

3. P. Grother, G. Quinn, M. Ngan, Face in Video Evaluation (Five) Face Recognition of Non-cooperative Subjects, Interagency Report 8173, National Institute of Standards and Technology, March 2017. https://doi.org/10.6028/NIST.IR.8173.

4. J. Yang, P. Ren, D. Chen, F. Wen, H. Li, G. Hua, Neural aggregation network for video face recognition, in: CVPR, In press, 2017.

5. O.M. Parkhi, A. Vedaldi, A. Zisserman, Deep face recognition, in: British Machine Vision Conference, vol. 1, 2015, pp. 1–12.

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