Calibrating Cameras in Poor-Conditioned Pitch-Based Sports Games
Rui Zeng, Ruan Lakemond, Simon Denman, Sridha Sridharan, Clinton Fookes, Stuart Morgan
Abstract
Camera calibration is a preliminary step in sports analytics which enables us to transform player positions to standard playing area coordinates. While many camera calibration systems work well when the visual content contains sufficient clues, such as a key frame, calibrating without such information, such as may be needed when processing footage captured by a coach from the sidelines or stands, is challenging. In this paper an innovative automatic camera calibration system, which does not make use of any key frames, is presented for sports analytics. The proposed system consists of three components: a robust linear panorama module, a playing area estimation module, and a homography estimation module. It can eliminate distortion and calibrate the camera in each frame simultaneously, using correspondences between pairs of consecutive frames. Experiments on real data evaluate the performance and demonstrate the robustness of the system.
BibTeX
@inproceedings{icassp2018_calibratingcamer,
title = {Calibrating Cameras in Poor-Conditioned Pitch-Based Sports Games},
author = {Rui Zeng and Ruan Lakemond and Simon Denman and Sridha Sridharan and Clinton Fookes and Stuart Morgan},
booktitle = {ICASSP 2018},
year = {2018}
}