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https://doi.org/10.1007/978-3-...
Part of book or chapter of book . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Computer Vision

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book 01 Jan 2024 English Publisher:Springer Nature Switzerland
Authors: Paul Breiding; Kathlén Kohn; Bernd Sturmfels;

doi: 10.1007/978-3-031-51462-3_13

Computer Vision

Abstract

AbstractThe field of computer vision studies how computers can gain understanding from images and videos, similar to human cognitive abilities. One of the classical challenges is to reconstruct a 3D object from images taken by several unknown cameras. While the resulting questions in multiview geometry [80] have a long history in computer vision, recent years have seen a confluence with ideas and algorithms from algebraic geometry.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
hybrid
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