Antoine Petit

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Works

RoDyMan project

Real-time tracking of 3D elastic objects with an RGB-D sensor

These works aim at tracking in real-time a 3D textureless object which undergoes large deformations such as elastic ones, and rigid motions, using the point cloud data provided by an RGB-D sensor. This solution is expected to be useful for enhanced manipulation of humanoid robotic systems for the RoDyMan project. Our framework relies on a prior visual segmentation of the object in the image. The segmented point cloud is registered first in a rigid manner and then by non-rigidly fitting the mesh, based on the Finite Element Method to model elasticity, and on geometrical point-to-point correspondences to compute external forces exerted on the mesh. The real-time performance of the system is demonstrated on synthetic and real data involving challenging deformations and motions

Tracking fractures of deformable objects in real-time with an RGB-D sensor

Based on the tracking method presented above, we introduce a method able to track in real-time a 3D elastic deformable objects which undergo fractures. 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 de- formations and fractures.