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.
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