Illumination and Expression Invariant Recognition Using SSIM Based Sparse Representation
The sparse representation technique has provided a new way of looking at object recognition. As we demonstrate in this paper, however, the mean-squared error (MSE) measure, which is at the heart of this technique, is not a very robust measure when it comes to comparing facial images, which differ significantly in luminance values, as it only performs pixel-by-pixel comparisons. This requires a significantly large training set with enough variations in it to offset the drawback of the MSE...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of the International Conference on Pattern Recognition (ICPR 2010)|
|01_Khwaja_Illumination_and_Expression_2010.pdf||1.17 MB||Adobe PDF||Request a copy|
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