ML Anthology

Applications of Deep Learning for Top-View Omnidirectional Imaging: A Survey

Jingrui Yu, Ana Cecilia Pérez Grassi, Gangolf Hirtz
CVPRW 2023 pp. 6421-6433
doi:10.1109/CVPRW59228.2023.00683 /cvprw/2023/yu2023cvprw-applications/

Abstract

A large field-of-view fisheye camera allows for capturing a large area with minimal numbers of cameras when they are mounted on a high position facing downwards. This top-view omnidirectional setup greatly reduces the work and cost for deployment compared to traditional solutions with multiple perspective cameras. In recent years, deep learning has been widely employed for vision related tasks, including for such omnidirectional settings. In this survey, we look at the application of deep learning in combination with omnidirectional top-view cameras, including the available datasets, human and object detection, human pose estimation, activity recognition and other miscellaneous applications.

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Cite

Text

Yu et al. "Applications of Deep Learning for Top-View Omnidirectional Imaging: A Survey." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2023. doi:10.1109/CVPRW59228.2023.00683

Markdown

[Yu et al. "Applications of Deep Learning for Top-View Omnidirectional Imaging: A Survey." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2023.](https://mlanthology.org/cvprw/2023/yu2023cvprw-applications/) doi:10.1109/CVPRW59228.2023.00683

BibTeX

@inproceedings{yu2023cvprw-applications,
  title     = {{Applications of Deep Learning for Top-View Omnidirectional Imaging: A Survey}},
  author    = {Yu, Jingrui and Grassi, Ana Cecilia Pérez and Hirtz, Gangolf},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2023},
  pages     = {6421-6433},
  doi       = {10.1109/CVPRW59228.2023.00683},
  url       = {https://mlanthology.org/cvprw/2023/yu2023cvprw-applications/}
}