Pan-tilt-zoom SLAM for Sports Videos
Jikai Lu (Zhejiang University), Jianhui Chen (University of British Columbia), Jim Little (University of British Columbia, Canada) AbstractWe present an online SLAM system specifically designed to track pan-tilt-zoom (PTZ) cameras in highly dynamic sports such as basketball and soccer games. In these games, PTZ cameras rotate very fast and players cover large image areas. To overcome these challenges, we propose to use a novel camera model for tracking and to use rays as landmarks in mapping. Rays overcome the missing depth in pure-rotation cameras. We also develop an online pan-tilt forest for mapping and introduce moving objects (players) detection to mitigate negative impacts from foreground objects. We test our method on both synthetic and real datasets. The experimental results show the superior performance of our method over previous methods for online PTZ camera pose estimation.
DOI
10.5244/C.33.60
https://dx.doi.org/10.5244/C.33.60
Files
Paper (PDF)Supplementary material (PDF)BibTeX
@inproceedings{BMVC2019,
title={Pan-tilt-zoom SLAM for Sports Videos},
author={Jikai Lu and Jianhui Chen and Jim Little},
year={2019},
month={September},
pages={60.1--60.14},
articleno={60},
numpages={14},
booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
publisher={BMVA Press},
editor={Kirill Sidorov and Yulia Hicks},
doi={10.5244/C.33.60},
url={https://dx.doi.org/10.5244/C.33.60}
}
title={Pan-tilt-zoom SLAM for Sports Videos},
author={Jikai Lu and Jianhui Chen and Jim Little},
year={2019},
month={September},
pages={60.1--60.14},
articleno={60},
numpages={14},
booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
publisher={BMVA Press},
editor={Kirill Sidorov and Yulia Hicks},
doi={10.5244/C.33.60},
url={https://dx.doi.org/10.5244/C.33.60}
}