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Face recognition by incremental learning

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4 Author(s)
Weimin Huang ; Inst. for Infocom Res., Singapore ; Beng Hai Lee ; Liyuan Li ; K. Leman

One of the important features for human machine interaction is its ability to recognize human faces. This paper presents a novel architecture suitable for real time robotic face recognition by learning a person's face incrementally, where the Gabor features at respective feature locations of a face are used to derive a similarity measurement. A face tracking followed by a clustering technique is used to learn a person's face appearance variance when the system interacts with the person. The recognition by learning proposed in this paper is similar to the partial memory incremental learning method, where we proposed a novel approach to the learning and updating process. Experiment shows significant improvement in the face recognition performance after learning over the time and with more interaction between a person and the system.

Published in:

Systems, Man and Cybernetics, 2003. IEEE International Conference on  (Volume:5 )

Date of Conference:

5-8 Oct. 2003