Please use this identifier to cite or link to this item: https://doi.org/10.1109/AFGR.2000.840642
Title: Pose invariant face recognition
Authors: Huang F.J.
Zhou Z.
Zhang H.-J.
Chen T. 
Issue Date: 2000
Publisher: IEEE Computer Society
Citation: Huang F.J., Zhou Z., Zhang H.-J., Chen T. (2000). Pose invariant face recognition. Proceedings - 4th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2000 : 245-250. ScholarBank@NUS Repository. https://doi.org/10.1109/AFGR.2000.840642
Abstract: In this paper, we describe a novel neural network architecture, which can recognize human faces with any view in a certain viewing angle range (fromy left 30 degrees to right 30 degrees out of plane rotation). View-specific eigenface analysis is used as the frontend of the system to extract features, and the neural network ensemble is used for recognition. Experimental results show that the recognition accuracy of our network ensemble is higher than conventional methods such as using a single neural network to recognize faces of a specific view.
Source Title: Proceedings - 4th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2000
URI: http://scholarbank.nus.edu.sg/handle/10635/146392
ISBN: 0769505805
9780769505800
DOI: 10.1109/AFGR.2000.840642
Appears in Collections:Staff Publications

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