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Erschienen in:
Image and Signal Sensors for Computing and Machine Vision: Developments to Meet Future Needs Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

8. Stereoscopic Vision Systems in Machine Vision, Models, and Applications

verfasst von : Luis Roberto Ramírez-Hernández, Julio Cesar Rodríguez-Quiñonez, Moisés J. Castro-Toscano, Daniel Hernández-Balbuena, Wendy Flores-Fuentes, Moisés Rivas-López, Lars Lindner, Danilo Cáceres-Hernández, Marina Kolendovska, Fabián N. Murrieta-Rico

Erschienen in: Machine Vision and Navigation

Verlag: Springer International Publishing

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Abstract

Stereoscopic vision systems (SVS) allow performing digital scene reconstruction through cameras. SVS process the obtained images by their cameras from a three-dimensional scene, identifying similarities between the images that correspond to the same scene and, finally, performing a reconstruction process. SVS can be differentiated by the number of cameras and the geometry used in their design. In this chapter, each SVS is classified by its number of cameras, so that it can be divided into binocular vision systems, where there are SVS of two cameras and multivision systems that consist of SVS of three or more cameras. The aim of this chapter is to provide useful information to students, teachers, and researchers who want to learn about the different methods and applications of SVS used in the industry and current research topics. Also, it will be useful for everyone who wants to implement an SVS and needs an introduction to several available options to use the most convenient according to the application.

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Vorheriges Kapitel Machine Vision System for Orchard Management
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Metadaten
Titel
Stereoscopic Vision Systems in Machine Vision, Models, and Applications
verfasst von
Luis Roberto Ramírez-Hernández
Julio Cesar Rodríguez-Quiñonez
Moisés J. Castro-Toscano
Daniel Hernández-Balbuena
Wendy Flores-Fuentes
Moisés Rivas-López
Lars Lindner
Danilo Cáceres-Hernández
Marina Kolendovska
Fabián N. Murrieta-Rico
Copyright-Jahr
2020
Buch
Machine Vision and Navigation

Print ISBN: 978-3-030-22586-5

Electronic ISBN: 978-3-030-22587-2

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-22587-2_8

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