Local Relation Map: A Novel Illumination Invariant Face Recognition Approach

Lian, Zhichao; Joo, Er Meng

doi:10.5772/51667

Cited by 2 publications

(1 citation statement)

References 12 publications

(40 reference statements)

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“…Recently, local methods came into focus again, partly due to their robustness against occlusion and variations in facial expressions. Local methods have two advantages compared to holistic methods [12, 13]. First, a face can be represented as a set of feature vectors extracted from local regions, resulting in lower-dimensional vectors.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Hybrid Face Recognition Algorithm Using PCA and GABOR Wavelets

Cho

Roberts

Jung

et al. 2014

International Journal of Advanced Robotic Systems

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With the rapid development of computers and the increasing, mass use of high-tech mobile devices, vision-based face recognition has advanced significantly. However, it is hard to conclude that the performance of computers surpasses that of humans, as humans have generally exhibited better performance in challenging situations involving occlusion or variations. Motivated by the recognition method of humans who utilize both holistic and local features, we present a computationally efficient hybrid face recognition method that employs dual-stage holistic and local feature-based recognition algorithms. In the first coarse recognition stage, the proposed algorithm utilizes Principal Component Analysis (PCA) to identify a test image. The recognition ends at this stage if the confidence level of the result turns out to be reliable. Otherwise, the algorithm uses this result for filtering out top candidate images with a high degree of similarity, and passes them to the next fine recognition stage where Gabor filters are employed. As is well known, recognizing a face image with Gabor filters is a computationally heavy task. The contribution of our work is in proposing a flexible dual-stage algorithm that enables fast, hybrid face recognition. Experimental tests were performed with the Extended Yale Face Database B to verify the effectiveness and validity of the research, and we obtained better recognition results under illumination variations not only in terms of computation time but also in terms of the recognition rate in comparison to PCA- and Gabor wavelet-based recognition algorithms.

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Section: Introductionmentioning

confidence: 99%

An Efficient Hybrid Face Recognition Algorithm Using PCA and GABOR Wavelets

Cho

Roberts

Jung

et al. 2014

International Journal of Advanced Robotic Systems

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Design of Fractional-Order Controller for Trajectory Tracking Control of a Non-holonomic Autonomous Ground Vehicle

Al-Mayyahi

Wang

Birch

2015

J Control Autom Electr Syst

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(2016) Design of fractional-order controller for trajectory tracking control of a non-holonomic autonomous ground vehicle. Journal of Control, Automation and Electrical Systems, 27 (1). pp. 29-42. ISSN 2195-3880 This version is available from Sussex Research Online: http://sro.sussex.ac.uk/57057/ This document is made available in accordance with publisher policies and may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the URL above for details on accessing the published version. Copyright and reuse:Sussex Research Online is a digital repository of the research output of the University.Copyright and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable, the material made available in SRO has been checked for eligibility before being made available.Copies of full text items generally can be reproduced, displayed or performed and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. Abstract A robust control technique is proposed to address the problem of trajectory tracking of an autonomous ground vehicle (AGV). This technique utilizes a fractional-order proportional integral derivative (FOPID) controller to control a non-holonomic autonomous ground vehicle to track the behaviour of the predefined reference path. Two FOPID controllers are designed to control the AGV's inputs. These inputs represent the torques that are used in order to manipulate the implemented model of the vehicle to obtain the actual path. The implemented model of the non-holonomic autonomous ground vehicle takes into consideration both of the kinematic and dynamic models. In additional, a particle swarm optimization (PSO) algorithm is used to optimize the FOPID controllers' parameters. These optimal tuned parameters of FOPID controllers minimize the cost function used in the algorithm. The effectiveness and validation of the proposed method have been verified through different patterns of reference paths using MATLAB-Simulink software package. The stability of fractional-order system is analysed. Also, the robustness of the system is conducted by adding disturbances due to friction of wheels during the vehicle motion.The obtained results of FOPID controller show the advantage and the performance of the technique in terms of minimizing path tracking error and the complement of the path following.B Auday Al-Mayyahi

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Local Relation Map: A Novel Illumination Invariant Face Recognition Approach

Cited by 2 publications

References 12 publications

An Efficient Hybrid Face Recognition Algorithm Using PCA and GABOR Wavelets

An Efficient Hybrid Face Recognition Algorithm Using PCA and GABOR Wavelets

Design of Fractional-Order Controller for Trajectory Tracking Control of a Non-holonomic Autonomous Ground Vehicle

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