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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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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)
Divisions : Surrey research (other units)
Authors :
Lu, C
Feng, G
Qing, C
Date : 2008
DOI : 10.1007/978-3-540-85563-7_21
Contributors :
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 12:25
Last Modified : 23 Jan 2020 17:50

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