论文标题
用于头盔安全的实时多对象检测
Real Time Multi-Object Detection for Helmet Safety
论文作者
论文摘要
国家橄榄球联盟和亚马逊网络服务联合通过Kaggle竞赛制定了最佳的运动伤害监视和缓解计划。 NFL希望通过它为每个头盔分配特定的球员，这将有助于准确地确定每个球员在整个足球比赛中的“暴露”。我们正在尝试实施一种基于计算机视觉的ML算法，能够通过跟踪信息来分配检测到的头盔影响以纠正玩家。我们的论文将解释自动跟踪玩家头盔及其碰撞的方法。这也将使他们能够回顾以前的戏剧并探索随着时间的推移曝光的趋势。
The National Football League and Amazon Web Services teamed up to develop the best sports injury surveillance and mitigation program via the Kaggle competition. Through which the NFL wants to assign specific players to each helmet, which would help accurately identify each player's "exposures" throughout a football play. We are trying to implement a computer vision based ML algorithms capable of assigning detected helmet impacts to correct players via tracking information. Our paper will explain the approach to automatically track player helmets and their collisions. This will also allow them to review previous plays and explore the trends in exposure over time.
