Üç boyutlu yüz nirengi noktaları bulan metodların karşılaştırılması.

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Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2008

Tezin Dili: İngilizce

Öğrenci: Mustafa Yağcıoğlu

Danışman: İLKAY ULUSOY

Özet:

Human identification systems are commonly used for security issues. Most of them are based on ID card. However, using an ID card for identification may not be safe enough since people may not have any protection against the theft. Another solution to the identification problem is to use iris or fingerprints. However, systems based on the iris or fingerprints need close interaction to identification machine. Identifying someone from his photograph overcomes all these problems which can be called as face recognition. Common face recognition systems are based on the 2D image recognition but success rates of these methods are strictly depending on the environment. Variations on brightness and pose, complex background are the main problems for 2D image recognition systems. At this point, three dimensional face recognition techniques gain importance. Although there are a lot of methods developed for 3D face recognition, many of them assume that face is not rotated and there is not any destructive (i.e. beard, moustache, hair, hat, and eyeglasses) on the face. However, identification needs to be done though these destructives. Basic step for the face recognition is the determination of the anchor points (i.e. nose tip, inner eye points). In this study, the goal is to implement previously proposed four face recognition methods based on anchor point detection; “Multimodal Facial Feature Extraction for Automatic 3D Face Recognition” , “Automatic Feature Extraction for Multiview 3D Face Recognition”, “Multiple Nose Region Matching for 3D Face Recognition under Varying Facial Expression”, “3D face detection using curvature analysis”, to compare the success rates of them for rotated and destructed images and finally to propose improvements on these methods.