Fabiano Petronetto

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Vector fields analysis traditionally distinguishes conservative (curl-free) from mass preserving (divergence-free) components. The Helmholtz-Hodge decomposition allows separating any vector field into the sum of three uniquely defined components: curl free, divergence free and harmonic. This decomposition is usually achieved by using mesh-based methods such(More)
This paper presents a new visually realistic animation technique for objects that melt and flow. It simulates viscoplas-tic properties of materials such as metal, plastic, wax, polymer and lava. The technique consists in modeling the object by the transition of a non–Newtonian fluid with high viscosity to a liquid of low viscosity. During the melting, the(More)
Simulations of viscoplastic materials are traditionally governed by continuum mechanics. The viscous behavior is typically modeled as an internal force, defined by diverse quantities. This work introduces a fluid model to simulate the viscoplastic effect of solid materials, such as plastic, wax, clay and polymer. Our method consists in modeling a solid(More)
We present a novel algorithm for 2D vector field reconstruction from sparse set of points–vectors pairs. Our approach subdivides the domain adaptively in order to make local piecewise polynomial approximations for the field. It uses partition of unity to blend those local approximations together, generating a global approximation for the field. The(More)
Fig. 1. The liquid rope coiling effect: our technique with SPH fluid particles (left), and the respective free surface (middle) and a real image of honey coiling (right) extracted from Flickr repository. Abstract—We present a novel meshfree technique for animating free surface viscous liquids with jet buckling effects, such as coiling and folding. Our(More)
Kernel-based methods have experienced a substantial progress in the last years, tuning out an essential mechanism for data classification, clustering and pattern recognition. The effectiveness of kernel-based techniques, though, depends largely on the capability of the underlying kernel to properly embed data in the feature space associated to the kernel.(More)