DocumentCode :
3213333
Title :
Face Recognition Using 3D Head Scan Data Based on Procrustes Distance
Author :
Mostayed, Ahmed ; Kim, Sikyung ; Mazumder, Mohammad Mynuddin Gani ; Park, Se Jin
Author_Institution :
Dept. of Electr. Eng., Kongju Nat. Univ., Kongju
fYear :
2008
fDate :
25-29 Feb. 2008
Firstpage :
203
Lastpage :
208
Abstract :
Recently face recognition has attracted significant attention from the researchers and scientists in various fields of research, such as biomedical informatics, pattern recognition, vision, etc due its applications in commercially available systems, defense and security purpose Face recognition presents a very challenging problem in real application in computer vision and pattern recognition due to variation of face. A large number of face recognition algorithms, along with their modifications are available over the past three decades. In this paper a practical method for face reorganization utilizing head cross section data based on Procrustes analysis is proposed. Firstly, a number of head cross section data were extracted from 3D head scanner along sagittal plane for eight different subjects. After extracting 3D head cross section data a comparison analysis were performed utilizing Procrustes distance to differentiate their face pattern from each other. The performance analysis of face recognition was analyzed based on K nearest neighbor classifier. The experimental results presented here verify that the proposed method is considerable effective.
Keywords :
face recognition; feature extraction; pattern classification; 3D head scan data; K nearest neighbor classifier; Procrustes distance; face recognition; Application software; Biomedical informatics; Computer security; Data mining; Data security; Face detection; Face recognition; Head; Pattern recognition; Performance analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Engineering Systems, 2008. INES 2008. International Conference on
Conference_Location :
Miami, FL
Print_ISBN :
978-1-4244-2082-7
Electronic_ISBN :
978-1-4244-2083-4
Type :
conf
DOI :
10.1109/INES.2008.4481295
Filename :
4481295
Link To Document :
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