A survey of Hough Transform
By Priyanka Mukhopadhyay, Bidyut Baran Chaudhuri. Pattern Recognition, 2015
1,060 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Media Technology
View Paper: https://www.semanticscholar.org/paper/272c8c8f72e7dca27c12afa30e11bf0784e8c39d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Hrvoje Benko
- Andrew D. Wilson
- Benjamin Nachman
- Kyle Cranmer
- Daniel Whiteson
- Michael Kagan
- B. MacIntyre
- S. Zambito
In Media Technology
- Kyle Cranmer
- Alexandre Boulch
- Atlas Collaboration
- Cong Yao
- Xiang Bai
- Jiri Matas
- Lukás Neumann
- Zhenwei Shi
Citations in the corpus
- Muon reconstruction and identification efficiency in ATLAS using the full Run 2 $pp$ collision data set at $\sqrt{s}=13$ TeV (2020, methodology): “Segments are identified in the individual stations by means of a Hough transform [30].”
- Processing (2020, neutral): “One outcome of research on extended practice is the accumulation of an enormous data base, the culling of which is a slow but steady process.”
- RoomAlive: magical experiences enabled by scalable, adaptive projector-camera units (2014, methodology): “The Hough transform [17] is used to select a finite set of planes.”
- HDMapNet: An Online HD Map Construction and Evaluation Framework (2021, neutral): “Hough transform [14]), image-to-world projection, etc.”
- Evidence for the associated production of the Higgs boson and a top quark pair with the ATLAS detector (2017, positive): “A Hough transform [71] is used to search for hits in the curvature plane of the toroidal magnetic field in the MDT, where a straight line fit is used to produce segments.”
- Muon reconstruction performance of the ATLAS detector in proton–proton collision data at s =13 TeV (2016, neutral): “form [17] is used to search for hits aligned on a trajectory”
- Deep Learning for Robust Normal Estimation in Unstructured Point Clouds (2016, background): “Shape hypotheses populate the bins of an ac-cumulator mapped onto this space, and the most densely populated bins identify the shapes to extract [DH72, IK88].”