向专业人士学习：从广播录像中提取专业守门员技术
Learning from the Pros: Extracting Professional Goalkeeper Technique from Broadcast Footage
摘要：
作为一个打草根足球的业余守门员，还有谁比顶级职业守门员更值得学习呢？在本文中，我们利用计算机视觉和机器学习模型来评估专业人员的储蓄技术，以供低级别人员学习。我们训练一个无监督的机器学习模型，使用从广播镜头中提取的3D身体姿势数据来学习专业守门员技术。在此基础上，提出了一个“期望扑救”模型，通过该模型可以确定不同比赛情境下守门员的最优扑救技术。
英文摘要：
As an amateur goalkeeper playing grassroots soccer, who better to learn from than top professional goalkeepers? In this paper, we harness computer vision and machine learning models to appraise the save technique of professionals in a way those at lower levels can learn from. We train an unsupervised machine learning model using 3D body pose data extracted from broadcast footage to learn professional goalkeeper technique. Then, an "expected saves" model is developed, from which we can identify the optimal goalkeeper technique in different match contexts.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
