  Given an image sequence featuring a portion of a sports field filmed by a
moving and uncalibrated camera, such as the one of the smartphones, our goal is
to compute automatically in real time the focal length and extrinsic camera
parameters for each image in the sequence without using a priori knowledges of
the position and orientation of the camera. To this end, we propose a novel
framework that combines accurate localization and robust identification of
specific keypoints in the image by using a fully convolutional deep
architecture. Our algorithm exploits both the field lines and the players'
image locations, assuming their ground plane positions to be given, to achieve
accuracy and robustness that is beyond the current state of the art. We will
demonstrate its effectiveness on challenging soccer, basketball, and volleyball
benchmark datasets.
