Fast and robust face recognition for incremental data

Authors:
I. Gede Pasek Suta Wijaya;Keiichi Uchimura;Gou Koutaki
Affiliations:
Computer Science and Electrical Engineering of GSST, Kumamoto University, Kumamoto Shi, Japan and Electrical Engineering Department, Faculty of Engineering, Mataram University, Mataram, West Nusa ...;Computer Science and Electrical Engineering of GSST, Kumamoto University, Kumamoto Shi, Japan;Computer Science and Electrical Engineering of GSST, Kumamoto University, Kumamoto Shi, Japan
Venue:
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume part II
Year:
2010

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Abstract

This paper proposes fast and robust face recognition system for incremental data, which come continuously into the system. Fast and robust mean that the face recognition performs rapidly both of training and querying process and steadily recognize face images, which have large lighting variations. The fast training and querying can be performed by implementing compact face features as dimensional reduction of face image and predictive LDA (PDLDA) as face classifier. The PDLDA performs rapidly the features cluster process because the PDLDA does not require to recalculate the between class scatter, Sb, when a new class data is registered into the training data set. In order to get the robust face recognition achievement, we develop the lighting compensation, which works based on neighbor analysis and is integrated to the PDLDA based face recognition.