loading
Papers

Research.Publish.Connect.

Paper

Authors: Carlos E. Thomaz 1 ; Gilson A. Giraldi 2 ; Duncan F. Gillies 2 and Daniel Rueckert 3

Affiliations: 1 FEI University Center, Brazil ; 2 National Laboratory of Scientific Computing, Brazil ; 3 Imperial College London, United Kingdom

ISBN: 978-989-758-361-2

Abstract: Faces are familiar objects that can be easily perceived and recognized by humans. However, the computational modeling of such apparently natural and heritable human ability remains challenging. This chapter shows theoretical and empirical results about the processes underlying face perception using frontal and well-framed images as stimuli. Exploring eye movements of a number of participants on distinct classification tasks, we have implemented a multivariate statistical method that combines variance information with focused human visual attention. Our experimental results carried out on publicly available face databases have indicated that we might emulate the face perception processing as a pattern-based coding scheme rather than a feature-based one to properly explain the proficiency of the human visual system in recognizing face information.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.214.184.124

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Thomaz C.; Giraldi G.; Gillies D.; Rueckert D. and (2017). Learning and Extracting Priori-driven Representations of Face Images to Understand the Human Visual Recognition System.In OPPORTUNITIES AND CHALLENGES for European Projects - Volume 1: EPS Portugal 2017/2018, ISBN 978-989-758-361-2, pages 42-55. DOI: 10.5220/0008861900420055

@conference{eps portugal 2017/201817,
author={Carlos E. Thomaz and Gilson A. Giraldi and Duncan F. Gillies and Daniel Rueckert},
title={Learning and Extracting Priori-driven Representations of Face Images to Understand the Human Visual Recognition System},
booktitle={OPPORTUNITIES AND CHALLENGES for European Projects - Volume 1: EPS Portugal 2017/2018,},
year={2017},
pages={42-55},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008861900420055},
isbn={978-989-758-361-2},
}

TY - CONF

JO - OPPORTUNITIES AND CHALLENGES for European Projects - Volume 1: EPS Portugal 2017/2018,
TI - Learning and Extracting Priori-driven Representations of Face Images to Understand the Human Visual Recognition System
SN - 978-989-758-361-2
AU - Thomaz, C.
AU - Giraldi, G.
AU - Gillies, D.
AU - Rueckert, D.
PY - 2017
SP - 42
EP - 55
DO - 10.5220/0008861900420055

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.