Three-dimensional self-organizing maps for classification of image properties
Udo Seiffert, B. Michaelis · 2002
The importance of analysing moving scenes within the wide area of digital image processing is increasingly high. Although a simple detection of object velocity by biological models has been considered in previously published papers (A. Tsukamoto et al., 1993; S. Wimbauer et al., 1994; J. Hogden et al., 1993), an implementation of artificial neural networks using a priori information for motion analysis is still quite rare. The paper shows the benefits from artificial neural networks and from using a priori information about the contents of the history in the image sequence to improve accuracy and speed of estimating motion parameters in the cases of distorted or overlapped objects. Firstly, it introduces 3 dimensional self organizing maps (SOM) with 2 dimensional input layers.