An Efficient Pose Tolerant Face Recognition Approach

SAMET R., Shokouh G. S., Baskurt K. B.

International Conference on Cyberworlds (CW), Santander, İspanya, 6 - 08 Ekim 2014, cilt.9550, ss.161-172 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 9550
  • Doi Numarası: 10.1007/978-3-662-49247-5_10
  • Basıldığı Şehir: Santander
  • Basıldığı Ülke: İspanya
  • Sayfa Sayıları: ss.161-172
  • Anahtar Kelimeler: Biometric pattern recognition, Face recognition, Principal component analysis, Feature extraction, Pose transformation learning, IMAGE
  • Ankara Üniversitesi Adresli: Evet

Özet

Face recognition is biometric pattern recognition, which is more acceptable and convenient for users compared with other biometric recognition traits. Among many problems in face recognition system, pose problem is considered as one of the major problem still unsolved in satisfactory level. This paper proposes a novel pose tolerant face recognition approach which includes feature extraction, pose transformation learning and recognition stages. In the first stage, 2DPCA is used as robust feature extraction technique. The linear regression is used as efficient and accurate transformation learning technique to create frontal face image from different posed face images in the second stage. In the last stage, Mahalanobis distance is used for recognition. Experiments on FERET and FEI face databases demonstrated the higher performance in comparison with traditional systems.