2013 CVPR CVPR 2013

Monocular Template-Based 3D Reconstruction of Extensible Surfaces with Local Linear Elasticity

Abstract

We propose a new approach for template-based extensible surface reconstruction from a single view. We extend the method of isometric surface reconstruction and more recent work on conformal surface reconstruction. Our approach relies on the minimization of a proposed stretching energy formalized with respect to the Poisson ratio parameter of the surface. We derive a patch-based formulation of this stretching energy by assuming local linear elasticity. This formulation unifies geometrical and mechanical constraints in a single energy term. We prevent local scale ambiguities by imposing a set of fixed boundary 3D points. We experimentally prove the sufficiency of this set of boundary points and demonstrate the effectiveness of our approach on different developable and non-developable surfaces with a wide range of extensibility.

🚀 Conference Pioneer — CVPR 2013
🌉 Interdisciplinary Bridge — Computer Vision and Machine Learning and Mathematics & Optimization
🧭 Keyword Pioneer — template-based reconstruction
🐣 Hot Topic Early Bird — surface reconstruction
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio