Abstract
In this work we investigate appearance-based methods for face recognition on image sequences from large head rotations in depth. We describe the computational difficulties in recognising faces undergoing large pose variations and evaluate the effectiveness of different linear appearance-based methods for the problem. A framework for modelling nonlinear face pose density distributions using Gaussian mixtures was proposed for face recognition under such conditions using general and modified Hyper Basis Function networks.
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© 1997 Springer-Verlag Berlin Heidelberg
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Gong, S., Ong, EJ., Loft, P.J. (1997). Appearance-based face recognition under large head rotations in depth. In: Chin, R., Pong, TC. (eds) Computer Vision — ACCV'98. ACCV 1998. Lecture Notes in Computer Science, vol 1352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63931-4_277
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DOI: https://doi.org/10.1007/3-540-63931-4_277
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