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

Jingrui Yu, Ana Cecilia Perez Grassi, Gangolf Hirtz; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2023, pp. 6421-6433

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 topview 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.

Related Material


[pdf] [arXiv]
[bibtex]
@InProceedings{Yu_2023_CVPR, author = {Yu, Jingrui and Grassi, Ana Cecilia Perez and Hirtz, Gangolf}, title = {Applications of Deep Learning for Top-View Omnidirectional Imaging: A Survey}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2023}, pages = {6421-6433} }