Inferring shape evolution

Luciano da Fontoura CostaAndrea G. Campos Bianchi

Dynamic shapes, namely shapes that change with time, represent an important issue in several scientific and technological contexts. The current article presents a model-based mathematic-computational approach for inferring the processes governing some of the most representative types of shape evolution. The considered models include functional mappings, convolution-based evolution and normal wavefront propagation. The methods are illustrated with respect to stationary (global) and non-stationary (local) dynamic evolutions, and the obtained results substantiate the potential of the presented methodology. Although concentrating on 2D shapes, the reported results can be extended to higher dimensional objects.

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