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Robotics 2018, 7(4), 69; https://doi.org/10.3390/robotics7040069

A Methodology for Multi-Camera Surface-Shape Estimation of Deformable Unknown Objects

Department of Mechanical and Industrial engineering, University of Toronto, 5 King’s College Road, Toronto, ON M5S3G8, Canada
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Received: 8 October 2018 / Revised: 4 November 2018 / Accepted: 8 November 2018 / Published: 11 November 2018
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Abstract

A novel methodology is proposed herein to estimate the three-dimensional (3D) surface shape of unknown, markerless deforming objects through a modular multi-camera vision system. The methodology is a generalized formal approach to shape estimation for a priori unknown objects. Accurate shape estimation is accomplished through a robust, adaptive particle filtering process. The estimation process yields a set of surface meshes representing the expected deformation of the target object. The methodology is based on the use of a multi-camera system, with a variable number of cameras, and range of object motions. The numerous simulations and experiments presented herein demonstrate the proposed methodology’s ability to accurately estimate the surface deformation of unknown objects, as well as its robustness to object loss under self-occlusion, and varying motion dynamics. View Full-Text
Keywords: deformable object; deformation estimation; shape recovery; computer vision; stereo vision; tracking; markerless deformable object; deformation estimation; shape recovery; computer vision; stereo vision; tracking; markerless
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Nuger, E.; Benhabib, B. A Methodology for Multi-Camera Surface-Shape Estimation of Deformable Unknown Objects. Robotics 2018, 7, 69.

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