| 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
V. Kr{\"{u}}ger
ABSTRACT
Wavelet networks (WNs) were introduced in 1992 as a combination of artificial neural radial basis function (RBF) networks and wavelet decomposition. Since then, however, WNs have received only little attention. We believe, that the potential of WNs has been generally underestimated. WNs have the advantage, that the wavelet coe±cients are directly related to the image data through the wavelet transform. In addition, the parameters of the wavelets in the WNs are subject to optimization, which results in a direct relation between the represented function and the optimized wavelets, leading to considerable data reduction (thus making subsequent algorithms much more e±cient) as well as to wavelets that can be used as an optimized filter bank. In this paper, we analyze some of their properties and hightlight their advantages for object representation purposes. We then present a series of experimental results where we have used WNs for face tracking in which we exploit the e±ciency due to data reduction, for face recognition and face-pose estimation where we exploit the optimized filter bank principle of the WNs. c °2002 Optical Society of America |
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