A new method for face detection in colour images for emotional bio-robots
A new method for face detection in colour images for emotional bio-robots
Emotional bio-robots have become a hot research topic in the last two decades. Though there has been some progress in the research, design and development of various emotional bio-robots, few of them can be used in practical applications. The study of emotional bio-robots demands multi-disciplinary co-operation. It involves computer science, artificial intelligence, 3D computation, engineering system modelling, analysis and simulation, bionics engineering, automatic control, image processing and pattern recognition etc. Among them, face detection belongs to image processing and pattern recognition. An emotional robot must have the ability to recognize various objects, particularly, it is very important for a bio-robot to be able to recognize human faces from an image. In this paper, a face detection method is proposed for identifying any human faces in colour images using the human skin model and eye detection method. Firstly, this method can be used to detect skin regions from the input colour image after normalizing its luminance. Then, all face candidates are identified using an eye detection method. Compared with existing algorithms, this method only relies on the colour and geometrical data of the human faces rather than using training datasets. From experimental results, it is shown that this method is effective and fast and it can be applied to the development of an emotional bio-robot with further improvements of its speed and accuracy.
bio-robots, eye detection, face detection, skin colour model
2983-2988
Zhang, Xu
21e210aa-51db-40af-a91b-f64bf44ed143
Zhang, Shujun
e918def5-c5a1-46a9-9946-6a5cd6ee986c
Hapeshi, Kevin
25dc6212-73d1-491b-a94e-92b2982a6721
1 November 2010
Zhang, Xu
21e210aa-51db-40af-a91b-f64bf44ed143
Zhang, Shujun
e918def5-c5a1-46a9-9946-6a5cd6ee986c
Hapeshi, Kevin
25dc6212-73d1-491b-a94e-92b2982a6721
Zhang, Xu, Zhang, Shujun and Hapeshi, Kevin
(2010)
A new method for face detection in colour images for emotional bio-robots.
Science China Technological Sciences, 53 (11), .
(doi:10.1007/s11431-010-4132-z).
Abstract
Emotional bio-robots have become a hot research topic in the last two decades. Though there has been some progress in the research, design and development of various emotional bio-robots, few of them can be used in practical applications. The study of emotional bio-robots demands multi-disciplinary co-operation. It involves computer science, artificial intelligence, 3D computation, engineering system modelling, analysis and simulation, bionics engineering, automatic control, image processing and pattern recognition etc. Among them, face detection belongs to image processing and pattern recognition. An emotional robot must have the ability to recognize various objects, particularly, it is very important for a bio-robot to be able to recognize human faces from an image. In this paper, a face detection method is proposed for identifying any human faces in colour images using the human skin model and eye detection method. Firstly, this method can be used to detect skin regions from the input colour image after normalizing its luminance. Then, all face candidates are identified using an eye detection method. Compared with existing algorithms, this method only relies on the colour and geometrical data of the human faces rather than using training datasets. From experimental results, it is shown that this method is effective and fast and it can be applied to the development of an emotional bio-robot with further improvements of its speed and accuracy.
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Accepted/In Press date: 10 August 2010
Published date: 1 November 2010
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Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
Keywords:
bio-robots, eye detection, face detection, skin colour model
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Local EPrints ID: 455830
URI: http://eprints.soton.ac.uk/id/eprint/455830
ISSN: 1674-7321
PURE UUID: 72f0cb19-5fb4-4b87-8d5e-886fa5ed0bce
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Date deposited: 05 Apr 2022 17:36
Last modified: 05 Jun 2024 17:41
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Author:
Shujun Zhang
Author:
Kevin Hapeshi
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