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The Computational Intelligence Research group of UNINOVA (CA3) main mission is to actively participate in applied research, supported by projects, by defining new concepts, methods and algorithms capable of solving real-world problems
Image tracking
This research aims to develop techniques for analyzing and tracking features (e.g. solar sunspots) and to develop a framework for their identification, characterization and tracking. The framework is being developed in a modular way to increase its extendibility and reusability. This research puts a special emphasis on solutions using evolutionary algorithms (e.g. hybrid of swarm intelligence and snake model algorithms) and fuzzy sets theory to allow optimizing the tracking of objects along time.

The snake model, also known as active contour model, is able to find the precise boundary of objects and it is widely used in segmentation, shape modeling, stereo matching and object tracking.

CA3 Relevant papers in this topic are (for more papers and downloads see publication section):

  • Shahamatnia, E., Dorotovic, I., Ribeiro, R. & Fonseca, J. (2012), "Towards an automatic sunspot tracking: Swarm intelligence and snake model hybrid", Acta Futura. Vol. 5, pp. 151-159.
  • Shahamatnia, E., Ayanzadeh, R., et al. (2011). Adaptive Imitation Scheme for Memetic Algorithms. In: Technological Innovation for Sustainability. Springer, pp. 109-116.
  • Shahamatnia, E., Dorotovic, I., et al. (2011). Swarm intelligence and snake model for automatic sunspot tracking. In AI in space: Intelligence beyond planet Earth workshop, 22nd International Joint Conference on Artificial Intelligence (IJCAI). Barcelona, Spain.
  • Shahamatnia, E. & Ebadzadeh, M.M. (2011). Application of particle swarm optimization and snake model hybrid on medical imaging. In 2011 IEEE Third International Workshop On Computational Intelligence In Medical Imaging. Paris, France: IEEE, pp. 1-8.

Apoio FCT – Fundação para a Ciência e a Tecnologia no âmbito da Unidade de Investigação CTS - Centro de Tecnologia e Sistemas, referência UIDB/00066/2020