Robust Projection onto Normalized Eigenspace Using Relative Residual Analysis and Optimal Partial Projection

Fumihiko SAKAUE  Takeshi SHAKUNAGA  

IEICE TRANSACTIONS on Information and Systems   Vol.E87-D   No.1   pp.34-41
Publication Date: 2004/01/01
Online ISSN: 
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Section on Machine Vision Applications)
Category: Reconstruction
eigenspace,  robust projection,  relative residual,  face recognition,  

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The present paper reports a robust projection onto eigenspace that is based on iterative projection. The fundamental method proposed in Shakunaga and Sakaue and involves iterative analysis of relative residual and projection. The present paper refines the projection method by solving linear equations while taking noise ratio into account. The refinement improves both the efficiency and robustness of the projection. Experimental results indicate that the proposed method works well for various kinds of noise, including shadows, reflections and occlusions. The proposed method can be applied to a wide variety of computer vision problems, which include object/face recognition and image-based rendering.