Player tracking data remains out of reach for many professional football
teams as their video feeds are not sufficiently high quality for computer
vision technologies to be used. To help bridge this gap, we present a method
that can estimate continuous full-pitch tracking data from discrete data made
from broadcast footage. Such data could be collected by clubs or players at a
similar cost to event data, which is widely available down to semi-professional
level. We test our method using open-source tracking data, and include a
version that can be applied to a large set of over 200 games with such discrete
data.

从广播镜头制作的离散数据中，我们提出一种方法来估计连续的全场跟踪数据，帮助球队和球员收集高质量的球员跟踪数据。

离散广播数据的连续足球运动员追踪

Continuous football player tracking from discrete broadcast data

This survey article summarizes research trends on the topic of anomaly
detection in video feeds of a single scene. We discuss the various problem
formulations, publicly available datasets and evaluation criteria. We
categorize and situate past research into an intuitive taxonomy and provide a
comprehensive comparison of the accuracy of many algorithms on standard test
sets. Finally, we also provide best practices and suggest some possible
directions for future research.

本论文总结了单一场景视频流异常检测的研究动向，包括问题表述、公开数据集、评估标准、算法比较和最佳实践，并提出未来研究的可能方向。