  In this work, an automatic and simple framework for hockey ice-rink
localization from broadcast videos is introduced. First, video is broken into
video-shots by a hierarchical partitioning of the video frames, and
thresholding based on their histograms. To localize the frames on the ice-rink
model, a ResNet18-based regressor is implemented and trained, which regresses
to four control points on the model in a frame-by-frame fashion. This leads to
the projection jittering problem in the video. To overcome this, in the
inference phase, the trajectory of the control points on the ice-rink model are
smoothed, for all the consecutive frames of a given video-shot, by convolving a
Hann window with the achieved coordinates. Finally, the smoothed homography
matrix is computed by using the direct linear transform on the four pairs of
corresponding points. A hockey dataset for training and testing the regressor
is gathered. The results show success of this simple and comprehensive
procedure for localizing the hockey ice-rink and addressing the problem of
jittering without affecting the accuracy of homography estimation.
