| ECVision indexed and annotated bibliography of cognitive computer vision publications This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1 The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
A. J. Howell and H. Buxton
ABSTRACT
This paper presents experiments using an adaptive learning compo nent based on Radial Basis Function (RBF) networks to tackle the unconstrained face recognition problem using low resolution video in formation. Firstly, we performed preprocessing of face images to mimic the effects of receptive field functions found at various stages of the hu man vision system. These were then used as input representations to RBF networks that learnt to classify and generalise over different views for a standard face recognition task. Two main types of preprocessing (Difference of Gaussian filtering and Gabor wavelet analysis) are com pared. Secondly we provide an alternative, `face unit' RBF network model that is suitable for largescale implementations by decomposi tion of the network, which avoids the unmanagability of neural net works above a certain size. Finally, we show the 2D shift, scale and yaxis rotation invariance properties of the standard RBF network. Quantitative and qualitative differences in these schemes are described and conclusions drawn about the best approach for real applications to address the face recognition problem using low resolution images. |
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