Computer Vision developments are enabling significant advances in many fields, including sports. Many applications built on top of Computer Vision technologies, such as tracking data, are nowadays essential for every top-level analyst, coach, and even player. In this paper, we survey Computer Vision techniques that can help many sports-related studies gather vast amounts of data, such as Object Detection and Pose Estimation. We provide a use case for such data: building a model for shot speed estimation with pose data obtained using only Computer Vision models. Our model achieves a correlation of 67%. The possibility of estimating shot speeds enables much deeper studies about enabling the creation of new metrics and recommendation systems that will help athletes improve their performance, in any sport. The proposed methodology is easily replicable for many technical movements and is only limited by the availability of video data.
翻译:在包括体育在内的许多领域,计算机愿景的发展正在促成重大进步。许多在计算机愿景技术之上建立的应用,例如跟踪数据,如今对于每一个顶级分析师、教练甚至运动员都至关重要。我们在本文件中调查了能够帮助许多体育相关研究收集大量数据的计算机愿景技术,例如物体探测和观光估计。我们为这些数据提供了一个使用实例:建立一个光速估计模型,仅使用计算机愿景模型提供数据。我们的模型实现了67%的关联性。估计射击速度的可能性使得能够进行更深入的研究,以创建新的计量和建议系统,帮助运动员在任何运动中提高业绩。提议的方法对于许多技术运动来说很容易复制,而且仅受到视频数据的提供的限制。