Calibrating narrow field of view soccer cameras is challenging because there are very few field markings in the image. Unlike previous solutions, we propose a two-point method, which requires only two point correspondences given the prior knowledge of base location and orientation of a pan-tilt-zoom (PTZ) camera. We deploy this new calibration method to annotate pan-tilt-zoom data from soccer videos. The collected data are used as references for new images. We also propose a fast random forest method to predict pan-tilt angles without image-to-image feature matching, leading to an efficient calibration method for new images. We demonstrate our system on synthetic data and two real soccer datasets. Our two-point approach achieves superior performance over the state-of-the-art method.
In REF , this problem is mitigated by using a two-point method.
A Two-Point Method for PTZ Camera Calibration in Sports
2018 IEEE Winter Conference on Applications of Computer Vision (WACV)
2018 IEEE Winter Conference on Applications of Computer Vision (WACV)
Computer Science