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arXiv · 2301.04037

ROBUSfT: Robust Real-Time Shape-from-Template, a C++ Library

Mohammadreza Shetab-Bushehri·Miguel Aranda·Youcef Mezouar·Adrien Bartoli·Erol Ozgur
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Abstract

Tracking the 3D shape of a deforming object using only monocular 2D vision is a challenging problem. This is because one should (i) infer the 3D shape from a 2D image, which is a severely underconstrained problem, and (ii) implement the whole solution pipeline in real-time. The pipeline typically requires feature detection and matching, mismatch filtering, 3D shape inference and feature tracking algorithms. We propose ROBUSfT, a conventional pipeline based on a template containing the object's rest shape, texturemap and deformation law. ROBUSfT is ready-to-use, wide-baseline, capable of handling large deformations, fast up to 30 fps, free of training, and robust against partial occlusions and discontinuity in video frames. It outperforms the state-of-the-art methods in challenging datasets. ROBUSfT is implemented as a publicly available C++ library and we provide a tutorial on how to use it in https://github.com/mrshetab/ROBUSfT

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Mohammadreza Shetab-Bushehri, Miguel Aranda, Youcef Mezouar, Adrien Bartoli, Erol Ozgur. 2023-01-10. ROBUSfT: Robust Real-Time Shape-from-Template, a C++ Library. https://doi.org/10.1016/j.imavis.2023.104867

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