Abstract
Self-organising neural networks preserves the topology of an input space by using their competitive learning. In this work we use a kind of self-organising network, the Growing Neural Gas, to represent non rigid objects as a result of an adaptive process by a topology-preserving graph that constitutes an induced Delaunay triangulation of their shapes. The neural network is used to build a system able to track image features in video image sequences. The system automatically keeps correspondence of features among frames in the sequence using its own structure.
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García-Rodríguez, J., Flórez-Revuelta, F., García-Chamizo, J.M. (2009). Visual Surveillance of Objects Motion Using GNG. In: Omatu, S., et al. Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. IWANN 2009. Lecture Notes in Computer Science, vol 5518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02481-8_35
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DOI: https://doi.org/10.1007/978-3-642-02481-8_35
Publisher Name: Springer, Berlin, Heidelberg
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