Real-Time Person Detection and Tracking in Panoramic Video
Abstract
The format agnostic production paradigm has been proposed to offer more engaging live broadcasts to the audience while ensuring the cost-efficiency of the production. An ultra-HD resolution panorama is captured, and streams for different devices and user profiles are semi-automatically generated. Information about person positions and trajectories in the video are important cues for making editing decisions for sports content. In this paper we describe a real-time person detection and tracking system for panoramic video. The approach extends our earlier tracking by detection algorithm by addressing a number of robustness issues that are especially relevant in sports content. The design of the approach is strongly driven by the requirement to process high-resolution video in real-time. We show that we can achieve improvements of the robustness of the algorithm while being able to perform real-time processing.
Cite
Text
Thaler and Bailer. "Real-Time Person Detection and Tracking in Panoramic Video." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2013. doi:10.1109/CVPRW.2013.149Markdown
[Thaler and Bailer. "Real-Time Person Detection and Tracking in Panoramic Video." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2013.](https://mlanthology.org/cvprw/2013/thaler2013cvprw-realtime/) doi:10.1109/CVPRW.2013.149BibTeX
@inproceedings{thaler2013cvprw-realtime,
title = {{Real-Time Person Detection and Tracking in Panoramic Video}},
author = {Thaler, Marcus and Bailer, Werner},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2013},
pages = {1027-1032},
doi = {10.1109/CVPRW.2013.149},
url = {https://mlanthology.org/cvprw/2013/thaler2013cvprw-realtime/}
}