NDLI: A fuzzy approximator with Gaussian membership functions to estimate a human's head pose

Content Provider	IEEE Xplore Digital Library
Author	Baradaran-K, M. Shekofteh, S.K. Toosizadeh, S. Akbarzadeh-T, M.-R.
Copyright Year	2010
Description	Author affiliation: Department of Artificial Intelligence, Islamic Azad University, Mashhad Branch, Mashhad, Iran (Baradaran-K, M.; Toosizadeh, S.) \|\| Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran (Shekofteh, S.K.; Akbarzadeh-T, M.-R.)
Abstract	Estimating the head pose plays an important role in computer vision and also as a key task for visual surveillance and face recognition applications hence a prominent problem in computer vision. Most of the works in this field suffer from lack of continuous estimating of the head pose and high accuracy. We know fuzzy systems as universal approximator capable of approximating an unknown function by having just few limited information while attaining high accuracy. In this paper, an improved approach is proposed for estimating the rotation angle of the head along horizontal axis based on a fuzzy approximator in which the membership functions are of Gaussian type. The proposed method is able to provide a continuous estimate of the head along horizontal axis with high accuracy, low computational cost while avoiding from getting involved into complex mathematical equations. Experiments on images from two standard well-known databases showed less than 6° of average absolute error in estimation which is a significant improvement over the approximator with simple triangular membership functions.
Starting Page	1154
Ending Page	1158
File Size	204331
Page Count	5
File Format	PDF
ISBN	9781424481347
e-ISBN	9781424481361
DOI	10.1109/ISDA.2010.5687029
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-11-29
Publisher Place	Egypt
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Conferences Estimation Gaussian Membership Function Magnetic heads Fuzzy approximator Approximation methods Face Head pose estimation Fuzzy systems
Content Type	Text
Resource Type	Article

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