Deformable surface 3D reconstruction from monocular images
By: Mathieu Salzmann, Pascal Fua
Contributors: Fua, Pascal
Series: Synthesis lectures on computer vision -- # 3
Publisher: Morgan & Claypool
Published: 2011
Place of publication: San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA)
Language: eng
Format: [electronic resource] /
ISBN-13: 9781608455843; 9781608455836
Subjects: Computer vision; Three-dimensional imaging; Deformation potential; Image reconstruction
Other titles: Synthesis digital library of engineering and computer science.
Description: Being able to recover the shape of 3D deformable surfaces from a single video stream would make it possible to field reconstruction systems that run on widely available hardware without requiring specialized devices. However, because many different 3D shapes can have virtually the same projection, such monocular shape recovery is inherently ambiguous. In this survey, we will review the two main classes of techniques that have proved most effective so far: The template-based methods that rely on establishing correspondences with a reference image in which the shape is already known, and non-rigid structure-from-motion techniques that exploit points tracked across the sequences to reconstruct a completely unknown shape. In both cases, we will formalize the approach, discuss its inherent ambiguities, and present the practical solutions that have been proposed to resolve them. To conclude, we will suggest directions for future research.
Notes: Part of: Synthesis digital library of engineering and computer science.

Series from website.

Includes bibliographical references (p. 83-97).

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

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Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.
Table of contents: title: 1. Introduction; title: 2. Early approaches to non-rigid reconstruction; title: Physics-based models; title: The finite element method; title: Physics-based methods for computer graphics; title: Physics-based methods for computer vision; title: Learned deformation models; title: Statistical learning methods; title: Learned models for non-rigid modeling; title: Regularization via shape parameterization; title: Legacy of the previous approaches; title: 3. Formalizing template-based reconstruction; title: Problem definition; title: Motivation; title: Camera models; title: 3D-to-2D correspondences; title: Linear formulation; title: Ambiguities under weak perspective projection; title: Ambiguities under full perspective projection; title: 4. Performing template-based reconstruction; title: Imposing temporal consistency; title: Imposing geometric constraints; title: Developable surfaces; title: Smooth surfaces; title: Distance constraints; title: 5. Formalizing non-rigid structure from motion; title: Problem definition; title: NRSFM under weak perspective projection; title: NRSFM under full perspective projection; title: Ambiguities of NRSFM; title: The missing data problem; title: 6. Performing non-rigid structure from motion; title: Orthonormality constraints; title: Imposing temporal consistency; title: From basis shapes to basis trajectories; title: Imposing geometric constraints; title: Global constraints; title: Local constraints; title: Splitting a global surface into local ones; title: 7. Future directions; title: Bibliography; title: Authors' biographies.