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PRL
2008

Illumination-robust face recognition using ridge regressive bilinear models

8 years 12 months ago
Illumination-robust face recognition using ridge regressive bilinear models
The performance of face recognition is greatly affected by illumination changes because intra-person variation of the captured images under different lighting conditions can be much bigger than the inter-person variation. This paper proposes an illumination-robust face recognition by separating an identity factor and an illumination factor using symmetric bilinear models. The translation procedure in the bilinear model requires a repetitive computation of matrix inverse operations to reach the identity and illumination factors. This computation may result in a non-convergent case when the observation has noisy information or the model is overfitted. To alleviate this situation, we suggest a ridge regressive bilinear model that combines the ridge regression into the bilinear model. This provides a number of advantages: it stabilizes the bilinear model by shrinking the range of identity and illumination factors appropriately and improves the recognition performance. Experimental results...
Dongsoo Shin, Hyung-Soo Lee, Daijin Kim
Added 28 Jan 2011
Updated 28 Jan 2011
Type Journal
Year 2008
Where PRL
Authors Dongsoo Shin, Hyung-Soo Lee, Daijin Kim
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