OCCLUSION INVARIANT FACE RECOGNITION USING TWO-DIMENSIONAL PCA

Tae Young Kim, Kyoung Mu Lee, Sang Uk Lee

2006

Abstract

Subspace analysis such as Principal Component Analysis(PCA) and Linear Discriminant Analysis(LDA) are widely used feature extraction methods for face recognition. However, most of them employ holistic basis so that local parts can not be efficiently represented in the subspace. Therefore, they cannot cope with occlusion problem. In this paper, we propose a new method using two-dimensional principal component analysis (2D PCA) for occlusion invariant face recognition. In contrast to PCA, 2D PCA is performed by projecting 2D image directly onto the 2D PCA subspace, and each row of feature matrix represents the distribution of corresponding row of the image. Therefore by classifying each row of the feature matrix independently, we can easily identify the locally occluded parts in the face image. The proposed occlusion invariant face recognition system consists of two steps: occlusion detection and partial matching. To detect occluded regions, we apply a new combined k-NN and 1-NN classifier to each row or block of the feature matrix of the test face. For partial matching, similarity between feature matrices is evaluated after removing the rows identified as the occluded parts. The experimental results on AR face database demonstrate that the proposed algorithm outperforms other existing approaches.

References

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Paper Citation


in Harvard Style

Young Kim T., Mu Lee K. and Uk Lee S. (2006). OCCLUSION INVARIANT FACE RECOGNITION USING TWO-DIMENSIONAL PCA . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 972-8865-40-6, pages 56-61. DOI: 10.5220/0001372500560061


in Bibtex Style

@conference{visapp06,
author={Tae Young Kim and Kyoung Mu Lee and Sang Uk Lee},
title={OCCLUSION INVARIANT FACE RECOGNITION USING TWO-DIMENSIONAL PCA},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},
year={2006},
pages={56-61},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001372500560061},
isbn={972-8865-40-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
TI - OCCLUSION INVARIANT FACE RECOGNITION USING TWO-DIMENSIONAL PCA
SN - 972-8865-40-6
AU - Young Kim T.
AU - Mu Lee K.
AU - Uk Lee S.
PY - 2006
SP - 56
EP - 61
DO - 10.5220/0001372500560061