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2018 | OriginalPaper | Chapter

Incremental Non-Rigid Structure-from-Motion with Unknown Focal Length

Authors : Thomas Probst, Danda Pani Paudel, Ajad Chhatkuli, Luc Van Gool

Published in: Computer Vision – ECCV 2018

Publisher: Springer International Publishing

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Abstract

The perspective camera and the isometric surface prior have recently gathered increased attention for Non-Rigid Structure-from-Motion (NRSfM). Despite the recent progress, several challenges remain, particularly the computational complexity and the unknown camera focal length. In this paper we present a method for incremental Non-Rigid Structure-from-Motion (NRSfM) with the perspective camera model and the isometric surface prior with unknown focal length. In the template-based case, we provide a method to estimate four parameters of the camera intrinsics. For the template-less scenario of NRSfM, we propose a method to upgrade reconstructions obtained for one focal length to another based on local rigidity and the so-called Maximum Depth Heuristics (MDH). On its basis we propose a method to simultaneously recover the focal length and the non-rigid shapes. We further solve the problem of incorporating a large number of points and adding more views in MDH-based NRSfM and efficiently solve them with Second-Order Cone Programming (SOCP). This does not require any shape initialization and produces results orders of times faster than many methods. We provide evaluations on standard sequences with ground-truth and qualitative reconstructions on challenging YouTube videos. These evaluations show that our method performs better in both speed and accuracy than the state of the art.

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Appendix
Available only for authorised users
Footnotes
1
 For most of the cameras, it is safe to assume that their intrinsics have no skew, unit aspect ratio, and a principal point close to the image center.
 
2
 The dataset was provided by the authors.
 
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Metadata
Title
Incremental Non-Rigid Structure-from-Motion with Unknown Focal Length
Authors
Thomas Probst
Danda Pani Paudel
Ajad Chhatkuli
Luc Van Gool
Copyright Year
2018
DOI
https://doi.org/10.1007/978-3-030-01261-8_46

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