• Title/Summary/Keyword: Ridge Regressive Bilinear Model

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Illumination Robust Face Recognition using Ridge Regressive Bilinear Models (Ridge Regressive Bilinear Model을 이용한 조명 변화에 강인한 얼굴 인식)

  • Shin, Dong-Su;Kim, Dai-Jin;Bang, Sung-Yang
    • Journal of KIISE:Software and Applications
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    • v.34 no.1
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    • pp.70-78
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    • 2007
  • The performance of face recognition is greatly affected by the illumination effect because intra-person variation under different lighting conditions can be much bigger than the inter-person variation. In this paper, we propose an illumination robust face recognition by separating identity factor and illumination factor using the symmetric bilinear models. The translation procedure in the bilinear model requires a repetitive computation of matrix inverse operation to reach the identity and illumination factors. Sometimes, this computation may result in a nonconvergent case when the observation has an noisy information. To alleviate this situation, we suggest a ridge regressive bilinear model that combines the ridge regression into the bilinear model. This combination provides some advantages: it makes the bilinear model more stable by shrinking the range of identity and illumination factors appropriately, and it improves the recognition performance by reducing the insignificant factors effectively. Experiment results show that the ridge regressive bilinear model outperforms significantly other existing methods such as the eigenface, quotient image, and the bilinear model in terms of the recognition rate under a variety of illuminations.