Abstract
The Topological Active Volumes is an active model focused on 3D segmentation tasks. It provides information about the surfaces and the inside of the detected objects in the scene. The segmentation process turns into a minimization task of the energy functions which control the model deformation. We used Differential Evolution as an alternative evolutionary method that minimizes the decisions of the designer with respect to other evolutionary methods such as genetic algorithms. Moreover, we hybridized Differential Evolution with a greedy search to integrate the advantages of global and local searches at the same time that the segmentation speed is improved. Moreover, we included in the local search the possibility of topological changes to perform a better adjustment in complex surfaces.
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Novo, J., Santos, J., Penedo, M.G. (2011). Differential Evolution Optimization of 3D Topological Active Volumes. In: Cabestany, J., Rojas, I., Joya, G. (eds) Advances in Computational Intelligence. IWANN 2011. Lecture Notes in Computer Science, vol 6691. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21501-8_35
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DOI: https://doi.org/10.1007/978-3-642-21501-8_35
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