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A growing neural gas algorithm with applications in hand modelling and tracking

Angelopoulou, Anastassia and Psarrou, Alexandra and Garcia Rodriguez, Jose (2011) A growing neural gas algorithm with applications in hand modelling and tracking. In: Cabestany, Joan and Rojas, Ignacio and Joya, Gonzalo, (eds.) Advances in Computational Intelligence: 11th International Work-Conference on Artificial Neural Networks, IWANN 2011, Torremolinos-Málaga, Spain, June 8-10, 2011, Proceedings, Part II. Lecture notes in computer science (6692). Springer, pp. 236-243.

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Official URL: http://dx.doi.org/10.1007/978-3-642-21498-1_30


Growing models have been widely used for clustering or topology learning. Traditionally these models work on stationary environments, grow incrementally and adapt their nodes to a given distribution based on global parameters. In this paper, we present an enhanced Growing Neural Gas (GNG) model for applications in hand modelling and tracking. The modified network consists of the geometric properties of the nodes, the underline local feature of the image, and an automatic criterion for maximum node growth based on the probability of the objects in the image. We present experimental results for hands and T1-weighted MRI images, and we measure topology preservation with the topographic product.

Item Type:Book Section
Research Community:University of Westminster > Electronics and Computer Science, School of
ID Code:9714
Deposited On:15 Sep 2011 12:49
Last Modified:25 Jul 2012 15:09

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