Title :
Face recognition using support vector machines and generalized discriminant analysis
Author :
Timotius, Ivanna K. ; Linasari, The Christiani ; Setyawan, Iwan ; Febrianto, Andreas A.
Author_Institution :
Dept. of Electron. Eng., Satya Wacana Christian Univ., Salatiga, Indonesia
Abstract :
Face recognition by machines has various important applications in our daily life. However, the task to teach machine to recognize face images has been a very challenging task. This paper presents face recognition by combining Generalized Discriminant Analysis (GDA) as a feature extractor and Support Vector Machines (SVM) as a classifier. Our experiment showed that the performance of combining these two methods as a face image classifier is better than by only using SVM. The accuracy of combined method is above 85%.
Keywords :
face recognition; feature extraction; image classification; learning (artificial intelligence); support vector machines; SVM; face image classifier; face recognition; feature extractor; generalized discriminant analysis; support vector machines; Accuracy; Face; Face recognition; Feature extraction; Kernel; Support vector machines; Vectors; Face Recognition; Generalized Discriminant Analysis; Support Vector Machines;
Conference_Titel :
Telecommunication Systems, Services, and Applications (TSSA), 2011 6th International Conference on
Conference_Location :
Bali
Print_ISBN :
978-1-4577-1441-2
DOI :
10.1109/TSSA.2011.6095397
