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Design and Implementation of a Facial Character Analysis Algorithm for Humanoid Robots

Published online by Cambridge University Press:  10 April 2019

Fatma Göngör  and
Önder Tutsoy
Fatma Göngör
Affiliation:
Electrical and Electronic Engineering Department, Adana Science and Technology University, Adana, Turkey. E-mail: [email protected]
Önder Tutsoy*
Affiliation:
Electrical and Electronic Engineering Department, Adana Science and Technology University, Adana, Turkey. E-mail: [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

Humanoid robots (HR) equipped with a sophisticated facial character analysis (FCA) algorithm can able to initiate crucial improvements in human–robot interactions. This paper, for the first time in the literature, proposes a three-stage FCA algorithm for the HR. At the initial stage of this algorithm, the HR detects the face with the Viola–Jones algorithm, and then important facial distance measurements are obtained with the geometric-based facial distance measurement technique. Finally, the measured facial distances are evaluated with the physiognomy science to reveal the characteristic properties of a person. Even though the proposed algorithm can be implemented to all HR, in this paper, it has been specifically applied to NAO HR. The reliability of the developed FCA algorithm is verified by analyzing each terminal decision about the character and its connection with the measured facial distances in the anatomy science.

Keywords

Geometric-based facial distance measurement techniqueFacial character analysisFeature extractionHuman–robot interactionNAO humanoid robotphysiognomy scienceViola–Jones algorithm
Type
Articles
Information
Robotica , Volume 37 , Issue 11 , November 2019 , pp. 1850 - 1866
Copyright
© Cambridge University Press 2019 

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