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Scene Flow Estimation from Light Fields via the Preconditioned Primal-Dual Algorithm Read chapter Read first chapter

2014 | OriginalPaper | Chapter

High-Resolution Stereo Datasets with Subpixel-Accurate Ground Truth

Authors : Daniel Scharstein, Heiko Hirschmüller, York Kitajima, Greg Krathwohl, Nera Nešić, Xi Wang, Porter Westling

Published in: Pattern Recognition

Publisher: Springer International Publishing

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Abstract

We present a structured lighting system for creating high-resolution stereo datasets of static indoor scenes with highly accurate ground-truth disparities. The system includes novel techniques for efficient 2D subpixel correspondence search and self-calibration of cameras and projectors with modeling of lens distortion. Combining disparity estimates from multiple projector positions we are able to achieve a disparity accuracy of 0.2 pixels on most observed surfaces, including in half-occluded regions. We contribute 33 new 6-megapixel datasets obtained with our system and demonstrate that they present new challenges for the next generation of stereo algorithms.

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previous chapter Introducing More Physics into Variational Depth–from–Defocus
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Metadata
Title
High-Resolution Stereo Datasets with Subpixel-Accurate Ground Truth
Authors
Daniel Scharstein
Heiko Hirschmüller
York Kitajima
Greg Krathwohl
Nera Nešić
Xi Wang
Porter Westling
Copyright Year
2014
Book
Pattern Recognition

Print ISBN: 978-3-319-11751-5

Electronic ISBN: 978-3-319-11752-2

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-319-11752-2_3

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