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Tracking Fractures of Deformable Objects in Real-Time with an RGB-D Sensor

Abstract : This paper introduces a method able to track in real-time a 3D elastic deformable objects which undergo fractures, using the point cloud data provided by an RGB-D sensor. Our framework relies on a prior visual segmentation of the object in the image. The segmented point cloud is registered by non-rigidly fitting the mesh, based on the Finite Element Method to physically model elasticity, and on geometrical point-to-point correspondences to compute external forces exerted on the mesh. Fractures are handled by processing the stress tensors computed on the mesh of the FEM model, in order to detect fracturable nodes. Local remeshing around fracturable nodes is then performed to propagate the fracture. The real-time performance of the system is demonstrated on real data involving various deformations and fractures.
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https://hal.archives-ouvertes.fr/hal-01617263
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Antoine Petit, Vincenzo Lippiello, Bruno Siciliano. Tracking Fractures of Deformable Objects in Real-Time with an RGB-D Sensor. 3D Vision (3DV), 2015 International Conference on, IEEE, Oct 2015, Lyon, France. pp.632 - 639, ⟨10.1109/3DV.2015.78⟩. ⟨hal-01617263⟩

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