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Authors: Cherinet G. Zewdie and Hubert Konik

Affiliation: Université de Lyon and Université Jean Monnet, France

ISBN: 978-989-758-074-1

Keyword(s): Human Visual System, Gender Recognition, Salient Region, HVS Inspired Gender Recognition, Local Binary Pattern.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Cognitive Systems ; Computational Intelligence ; Data Manipulation ; Evolutionary Computing ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing ; Symbolic Systems ; Vision and Perception

Abstract: A face reveals a great deal of information to a perceiver including gender. Humans use specific information (cue) from a face to recognize gender. The focus of this paper is to find out this cue when the Human Visual System (HVS) decodes gender of a face. The result can be used by a Computer Vision community to develop HVS inspired framework for gender recognition. We carried out a Pyscho-visual experiment to find which face region is most correlated with gender. Eye movements of 15 observers were recorded using an eye tracker when they performed gender recognition task under controlled and free viewing condition. Analysis of the eye movement shows that the eye region is the most correlated with gender recognition. We also proposed a HVS inspired automatic gender recognition framework based on the Psycho-visual experiment. The proposed framework is tested on FERET database and is shown to achieve a high recognition accuracy.

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Paper citation in several formats:
G. Zewdie, C. and Konik, H. (2015). Human Visual System Based Framework For Gender Recognition.In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-074-1, pages 254-260. DOI: 10.5220/0005176102540260

author={Cherinet G. Zewdie. and Hubert Konik.},
title={Human Visual System Based Framework For Gender Recognition},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},


JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Human Visual System Based Framework For Gender Recognition
SN - 978-989-758-074-1
AU - G. Zewdie, C.
AU - Konik, H.
PY - 2015
SP - 254
EP - 260
DO - 10.5220/0005176102540260

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