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In recent years, statistically motivated approaches for the registration and tracking of non-rigid objects, such as the Active Appearance Model (AAM), have become very popular. A major drawback of these approaches is that they require manual annotation of all training images which can be tedious and error prone. In this paper, a MPEG-4 based approach for(More)
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 lu-minance values, as it only performs(More)
A neuro-physiologically inspired model is presented for the contrast enhancement of images. The contrast of an image is calculated using simulated on-and off-centre receptive fields whereby obtaining the corresponding two contrast maps. We propose an adaptive asymmetric gain control function that is applied to the two contrast maps which are then used to(More)
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