Real-time ensemble based face recognition system for NAO humanoids using local binary pattern

Real-time ensemble based face recognition system for NAO humanoids using local binary pattern NAO humanoid robots are being used in many human-robot interaction applications. One of the important existing challenges is developing an accurate real-time face recognition system which does not require to have high computational cost. In this research work a real-time face recognition system by using block processing of local binary patterns of the face images captured by NAO humanoid is proposed. Majority voting and best score ensemble approaches have been used in order to boost the recognition results obtained in different colour channels of YUV colour space, which is a default colour space provided by the camera of NAO humanoid. The proposed method has been adopted on NAO humanoid and tested under real-world conditions. The recognition results were boosted in the real-time scenario by employing majority voting on the intra-sequence decisions with window size of 5. The experimental results are showing that the proposed face recognition algorithm overcomes the conventional and state-of-the-art techniques. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Analog Integrated Circuits and Signal Processing Springer Journals

Real-time ensemble based face recognition system for NAO humanoids using local binary pattern

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Publisher
Springer US
Copyright
Copyright © 2017 by Springer Science+Business Media, LLC
Subject
Engineering; Circuits and Systems; Electrical Engineering; Signal,Image and Speech Processing
ISSN
0925-1030
eISSN
1573-1979
D.O.I.
10.1007/s10470-017-1006-3
Publisher site
See Article on Publisher Site

Abstract

NAO humanoid robots are being used in many human-robot interaction applications. One of the important existing challenges is developing an accurate real-time face recognition system which does not require to have high computational cost. In this research work a real-time face recognition system by using block processing of local binary patterns of the face images captured by NAO humanoid is proposed. Majority voting and best score ensemble approaches have been used in order to boost the recognition results obtained in different colour channels of YUV colour space, which is a default colour space provided by the camera of NAO humanoid. The proposed method has been adopted on NAO humanoid and tested under real-world conditions. The recognition results were boosted in the real-time scenario by employing majority voting on the intra-sequence decisions with window size of 5. The experimental results are showing that the proposed face recognition algorithm overcomes the conventional and state-of-the-art techniques.

Journal

Analog Integrated Circuits and Signal ProcessingSpringer Journals

Published: Jun 28, 2017

References

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