Jean-Luc Peyrot

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We present a new direct Poisson disk sampling for surface meshes. Our objective is to sample triangular meshes, while satisfying good blue noise properties, but also preserving features. Our method combines a feature detection technique based on vertex curvature, and geodesic-based dart throwing. Our method is fast, automatic, and experimental results prove(More)
We propose in this paper a novel sampling method and an improvement of a spectral analysis tool that both handle complex shapes and sharp features. Starting from an arbitrary triangular mesh, our algorithm generates a new sampling pattern that exhibits blue noise properties. The fidelity to the original surface being essential, our algorithm preserves sharp(More)
Our objective is to include in stereoscopic 3D acquisition systems new technologies to automatically detect deformations on aircraft fuselages. We propose in this paper a semiregular mesh reconstruction dedicated to stereoscopic scanners, combined to a multiresolution analysis tool that detects dents on smooth surfaces. The proposed technique for(More)
We propose in this paper a robust simplification technique , which preserves geometric features such as sharp edges or corners from original surfaces. To achieve this goal, our simplification process relies on a detection tool that enables to preserve the sharp features during the three subsequent steps: a Poisson disk sampling that intelligently reduces(More)
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