This tutorial presents a hands-on view of the field of multi-view stereo with a focus on practical algorithms. Multi-view stereo algorithms are able to construct highly detailed 3D models from images alone. They take a possibly very large set of images and construct a 3D plausible geometry that explains the images under some reasonable assumptions, the most important being scene rigidity. The tutorial frames the multi-view stereo problem as an image/geometry consistency optimization problem. It describes in detail its main two ingredients: robust implementations of photometric consistency measures, and efficient optimization algorithms. It then presents how these main ingredients are used by some of the most successful algorithms, applied into real applications, and deployed as products in the industry. Finally it describes more advanced approaches exploiting domain-specific knowledge such as structural priors, and gives an overview of the remaining challenges and future research directions.
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25 June 2015
Research Article|
June 25 2015
Multi-View Stereo: A Tutorial Available to Purchase
Yasutaka Furukawa;
Yasutaka Furukawa
Washington University in St. Louis
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Carlos Hernández
Carlos Hernández
Google Inc.
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Online ISSN: 1572-2759
Print ISSN: 1572-2740
© 2015 Y. Furukawa and C. Hernández
2015
Y. Furukawa and C. Hernández
Licensed re-use rights only
Foundations and Trends in Computer Graphics and Vision (2015) 9 (1-2): 1–148.
Citation
Furukawa Y, Hernández C (2015), "Multi-View Stereo: A Tutorial". Foundations and Trends in Computer Graphics and Vision, Vol. 9 No. 1-2 pp. 1–148, doi: https://doi.org/10.1561/0600000052
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