Classification of facial expressions by using 2D empirical mode decomposition

Abstract

Ozetge-Bu �ah�mada, altl temel yiiz ifadesini tespit i�in iki boyutlu Gorgiil Kip AYrl�lmml (2B-GKA) kullanan bir yontem sunulmaktadlr. Duygu durumunu temsil eden yiiz imgelerinden iist ve alt yiiz bOigeleri klrpllarak 2B-GKA uygulanml� ve her bir bOigeye kar�lhk ii� Ozgiil Kip Fonksiyonu (OKF) ile bir artlk imge elde edilmi�tir. Yiiz ifadesini temsil eden sekiz alt imgede etkili frekans bolgesini tespit etmek amaclyla fark!! bant geni�liklerine sahip siizge�ler tasarlanml� ve etkileri gozlemlenmi�tir. Smltlandlrma i�in ozniteliklerin elde edilmesinde alt imgelerden hesaplanan istatistiksel metrikler ve ikinci yakla�lm olarak Radon Donii�iimii kullamlml�tlr. Olu�turulan nitelik vektOrleri Destek Vektor Makineleri ile slmtlandlrllml�tlr. iki yakla�lm i�in bulunan sonu�lar kar�lla�tlrllml�tlr. Anahtar Kelimeler -yuz ijadeleri; eylem birimleri; gorgUl kip ayrl §lml; radon donu §umU. Abstract-In this study, we present a method to estimate six basic facial expressions of a person by applying 2dimensional Empirical Mode Decomposition (2D-EMD) on face images which represent the emotional state. Three intrinsic mode functions (IMF) and a residue is obtained by applying 2D-EMD to each facial regions that are cropped from upper and lower face regions. Filters having different bandwidths are designed to detect the efficient frequency band of all eight sub-images. Two approaches are used to calculate the features: statistical metrics of each sub-image, and Radon Transform of sub-images are used as features in classification. Support Vector Machines classifier is used as to identify the facial expression. The results for the two feature vector approaches are presented and compared.