Quantification of the effect of symmetry in face perception

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Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Enformatik Enstitüsü, Sağlık Bilişimi Anabilim Dalı, Türkiye

Tezin Onay Tarihi: 2008

Öğrenci: NAHİDE DİCLE DÖVENCİOĞLU

Danışman: DİDEM GÖKÇAY

Özet:

Facial symmetry has been a central component in many studies on face perception. The relationship between bilateral symmetry and subjective judgments on faces is still arguable in the literature. In this study, a database of natural looking face images with different levels of symmetry is constructed using several digital preprocessing and morphing methods. Our aim is to investigate the correlations between quantified asymmetry, perceived symmetry and a subjective judgment: ‘attractiveness’. Images in the METU-Face Database are built to represent three levels of symmetry (original, intermediate, and symmetrical) within five classes which also represent the orientation of bilateral symmetry: left versus right. In addition, the asymmetry of original images is quantified using a landmark-based method. Based on the theory of holistic face perception, we introduce a novel method to quantify facial asymmetry wholesomely: Entropybased quantification. In Experiment 1 and 2, images were rated on attractiveness judgments and on perceived symmetry, respectively. Results indicate that landmark-based quantifications were not sufficient to account for perceived symmetry ratings (SRs), but they revealed that as the vertical deviation of the symmetry decreases, attractiveness rating (AR) collected from that face increases. Moreover, morphing classes and their relationship to both ARs and SRs were highly correlated. Consistent with the previously done research, symmetrical images were found more attractive. We found that although ARs were the same for left versus right composites, for SRs, there is a significant difference between left and right. Finally, a more elucidative quantification approach for subjective face perception is achieved through significant correlations of entropy scores with both ARs and SRs.