Title :
3D Face Recognition Based on Pose Correction Using Euler Angle Method
Author :
Panchal, Kiran ; Shah, Hemal
Author_Institution :
Inf. Technol. Dept., G.H. Patel Coll. of Eng. & Technol., Vallabh Vidyanagar, India
Abstract :
Face recognition is one of the biometric method, to identification of given face image using main features of the face. 3D face recognition approach handles the challenges of 2D face recognition such as pose, illumination, expression, etc in a better way. The exploration of 3D face recognition is widely used for security at many places like airport, organizations, crime detection etc. uncontrolled condition of real-world biometric applications is pose which is a great challenge to any face recognition approach. Such pose variations can cause extensive occlusions, resulting in missing data. This work presents 3D face recognition method which is invariant to pose. The method handles pose correction problem with rotation matrix based on Euler angle. Further dimensionality of face image is reduced by the principal component analysis and the recognition is done by the Euclidean distance algorithm. we used GAVAB 3D face database for simulation and measured performance like Recognition rate, False acceptance rate (FAR), False rejection rate (FRR) and Equal error rate (EER) are used to evaluate performance of the method. We have achieved 1.12 % improvement in Recognition rate and 0.15% improvement in equal error rate for probes with neutral and non-neutral, respectively.
Keywords :
face recognition; feature extraction; matrix algebra; pose estimation; principal component analysis; 2D face recognition; 3D face recognition; EER; Euclidean distance algorithm; Euler angle method; FAR; FRR; GAVAB 3D face database; biometric method; equal error rate; face features; face image dimensionality reduction; face image identification; facial expression; false acceptance rate; false rejection rate; illumination; occlusions; pose correction problem; pose variations; principal component analysis; recognition rate; rotation matrix; security; Databases; Face; Face recognition; Solid modeling; Support vector machine classification; Three-dimensional displays; Vectors; Face Recognition; Pose Correction; principal component analysis;
Conference_Titel :
Machine Intelligence and Research Advancement (ICMIRA), 2013 International Conference on
Conference_Location :
Katra
DOI :
10.1109/ICMIRA.2013.99