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A manifolded AdaBoost for face recognition

Lu, C, Jiang, J, Feng, G and Qing, C (2008) A manifolded AdaBoost for face recognition In: 12th International Conference, KES 2008, 2008-09-03 - 2008-09-05, Zagreb, Croatia.

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Abstract

Manifold learning is an effective dimension reduction method to extract nonlinear structures from high dimensional data. Recently, manifold learning started to attract attention within the research communities of image analysis, computer vision, and document data analysis. In this paper, we propose a Manifolded AdaBoost algorithm towards automatic 2D face recognition by using AdaBoost to fold the manifold space dimension and exploit the strength of both techniques. Experimental results support that the proposed algorithm improve over existing benchmarks in terms of stability and recognition precision rates.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Authors :
NameEmailORCID
Lu, CUNSPECIFIEDUNSPECIFIED
Jiang, Jjianmin.jiang@surrey.ac.ukUNSPECIFIED
Feng, GUNSPECIFIEDUNSPECIFIED
Qing, CUNSPECIFIEDUNSPECIFIED
Date : 2008
Identification Number : 10.1007/978-3-540-85563-7_21
Contributors :
ContributionNameEmailORCID
publisherSpringer, UNSPECIFIEDUNSPECIFIED
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 12:25
Last Modified : 17 May 2017 15:03
URI: http://epubs.surrey.ac.uk/id/eprint/835269

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