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Register a new userFace Expression Classification Using Neural Network and PCA algorithm
تصنيف تعابير الوجه باستخدام شبكة عصبية وخوارزمية PCA
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الغاية من هذا المقال إلقاء الضوء على آلية ومراحل عمل نظام خبير , يقوم بتحديد انتماء وجه مدخل الى أي من تعابير الوجه الستة النموذجية وهي الغضب , الاشمئزاز , الخوف , السعادة , الحزن , الدهشة بالإضافة إلى الحالة الطبيعية . وذلك بتطبيق خوارزمية تحليل المكونات الأساسية PCA- principal component analysis , والمتعلقة بالعناصر الثلاث العين والحاجب والفم , خلافا للدراسات المعهودة في هذا المجال التي تعتمد على الوجه بالكامل. هذه القيم الناتجة تستخدم في تحديد شعاع صفات الوجه كقيم لدخل الشبكة العصبونية , ويتم تدريب الشبكة العصبونية باستخدام خوارزمية الانتشار الخلفي . علما أن الوجوه المستخدمة تعود لأشخاص من أعمار وعروق مختلفة .
The purpose of this article is to shed light on the mechanism and the procedures of a program that classifies an input face into any of the six basic facial expressions, which are Anger, Disgust, Fear, Happiness, Sadness and Surprise, in addition to normal face. This program works by apply PCA- principal component analysis algorithm, which is applied of one side of the face, and depends, on contrast to the traditional studies which rely on the whole face, on three components: Eyebrows, Eyes and Mouth. Those out-value are used to determine the facial feature array as an input to the neural network, and the neural network is trained by using the back-propagation algorithm. Note that the faces used in this study belong to people from different ages and races.
References used
CALDER A, BURTON A, MILLER P, YOUNG A, AKAMATSU S, 2001- A principal component analysis of facial expressions. Vision Research 41 (2001) 1179–1208
DAILEY M, COTTRELL G,1999- PCA = Gabor for Expression Recognition. Computer Science and Engineering, University of California, San Diego
THAI L,NGUYEN N, HAI T, Member, IACSIT,2011- A Facial Expression Classification System Integrating Canny, Principal Component Analysis and Artificial Neural Network. International Journal of Machine Learning and Computing, Vol. 1, No. 4
GARG A, CHOUDHARY V, 2012- facial expression recognition using principal component analysis. International Journal of Scientific Research Engineering &Technology , Volume 1 Issue4, pp 039-042
GOSAVI A, KHOT S, 2013- Facial Expression Recognition Using Principal Component Analysis. International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-3, Issue-4
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