论文标题
敲门。谁在那里？ - 通过合成数据识别足球运动员球衣数字
Knock, knock. Who's there? -- Identifying football player jersey numbers with synthetic data
论文作者
论文摘要
自动播放器识别是体育视频分析中必不可少且复杂的任务。多年来，已经制定了不同的策略，但是鉴于其多功能性和相对简单性，基于泽西岛数字的识别是最常见的方法之一。但是，由于摄像头的变化，视频分辨率低，宽范围镜头的小对象大小以及玩家的姿势和移动的瞬态变化，泽西岛数字的自动检测仍然具有挑战性。在本文中，我们在西雅图海鹰队练习视频的一个小型，高度不平衡的数据集中介绍了针对球衣号码识别的新颖方法。我们的结果表明，简单的模型可以在泽西岛数字检测任务上实现可接受的性能，并且合成数据可以显着提高性能（准确性增加了〜9％，总数〜18％，低频数量）使我们的方法达到了最新的结果。
Automatic player identification is an essential and complex task in sports video analysis. Different strategies have been devised over the years, but identification based on jersey numbers is one of the most common approaches given its versatility and relative simplicity. However, automatic detection of jersey numbers is still challenging due to changing camera angles, low video resolution, small object size in wide-range shots and transient changes in the player's posture and movement. In this paper we present a novel approach for jersey number identification in a small, highly imbalanced dataset from the Seattle Seahawks practice videos. Our results indicate that simple models can achieve an acceptable performance on the jersey number detection task and that synthetic data can improve the performance dramatically (accuracy increase of ~9% overall, ~18% on low frequency numbers) making our approach achieve state of the art results.
