Abstract
Most research on face recognition has focused so far on identification from full frontal/profile facial images. We have reported earlier on a study that assesses the usefulness of partial faces for face recognition. We expand on our earlier results as we now assess if face recognition performance changes if the left half or the right half of the face is chosen for analysis. Our approach employs Ensemble of Radial Basis Functions (ERBF) networks. The motivation for ERBF comes from their ability to cope with the inherent variability in the image formation and data acquisition process. The database used to assess the comparative merit of the left vs. right half of the face consists of face images from 150 different subjects. The subjects pose across ±5° rotation for a total of 3,000 images. The experimental results, using average Cross Validation performance, indicate that there is no significant difference if the left half (96%) or the right half (94%) of the face is used.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Wechsler, H., Phillips, P.J., Bruce, V., Soulie, F.F., Huang, T.S. (eds.): Face Recognition: From Theory to Applications. Springer, New York (1998)
Gong, S., McKenna, S.J., Psarrou, A.: Dynamic Vision: From Images to Face Recognition, 1st edn. Imperial College Press, London (2000)
Turk, M., Pentland, A.: Eigenfaces for Recognition. Int. J. Cognitive Neuroscience 3, 71–86 (1991)
Wiskott, L., Fellous, J.M., Krüger, N., Malsburg, C.: Face Recognition by Elastic Graph Matching. IEEE PAMI 19(7), 775–779 (1996)
Etemad, K., Chellappa, R.: Discriminant Analysis for Recognition of Human Face Images. J. Optical Society of America 14, 1724–1733 (1997)
Gutta, S., Wechsler, H.: Face Recognition using Hybrid Classifiers. Int. J. Pattern Recognition 30(4), 539–553 (1997)
Sato, K., Shah, S., Aggarwal, J.K.: Partial Face Recognition using Radial Basis Function networks. In: Proc. of the 3rd International Conference on Face and Gesture Recognition, Nara, Japan, pp. 288–293 (1998)
Gutta, S., Philomin, V., Trajkovic, M.: An Investigation into the use of Partial Faces for Face Recognition. In: Proc. of the 5th International Conference on Face and Gesture Recognition, Washington D.C., USA, pp. 33–38 (2002)
Colmenarez, A., Frey, B., Huang, T.S.: Detection and Tracking of Faces and Facial Features. In: Proc. of International Conference on Image Processing, Kobe, Japan, pp. 268–272 (1999)
Lippmann, R.P., Ng, K.: A Comparative Study of the Practical Characteristic of Neural Networks and Pattern Classifiers, MIT Lincoln Labs. Tech. Report 894 (1991)
Weiss, S.M., Kulikowski, C.A.: Computer Systems That Learn. Morgan Kaufmann, San Francisco (1991)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gutta, S., Wechsler, H. (2003). Partial Faces for Face Recognition: Left vs Right Half. In: Petkov, N., Westenberg, M.A. (eds) Computer Analysis of Images and Patterns. CAIP 2003. Lecture Notes in Computer Science, vol 2756. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45179-2_77
Download citation
DOI: https://doi.org/10.1007/978-3-540-45179-2_77
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40730-0
Online ISBN: 978-3-540-45179-2
eBook Packages: Springer Book Archive