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Artificial Intelligence for the automation of robotic cameras in live sports

机译:用于现场体育机器人摄像头自动化的人工智能

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The demand to cover lower tier sports games is rising rapidly. Unfortunately, it is economically not viable to deploy the traditional production methods, crews and equipment that we know for higher tier sports events. Production approaches requiring much less people are needed. For the last few years, high quality single man operated equipment combining replay video mixing, graphical insertions, … are being introduced. However, one still needs cameramen to operate the different cameras around the sports field. — In this paper we present the concept of a fully automated system creating multiple camera feeds via a series of robotic cameras. These robotic cameras are not human operated but piloted by an Artificial Intelligence based system. This system analyses the complete sports scene for relevant items to capture and uses that information to individually steer the different robotic cameras to generate the desired different camera views. More concretely, the AI backed system points, in real-time, the different robotic cameras to the relevant parts of the game and applies the appropriate zoom factor corresponding to the desired camera views. We will show first results of a prototype system applied to a soccer game. — To further push the limits of automating the production, the automatic camera operation is complemented with an automatic selection of the most interesting camera angle out of the available camera feeds. This automatic direction can either be used to create a fully automatic system or to assist the single operator in charge of a complete multi-camera production. First experiments indicate that the quality of the camera selection comes close to the judgement of real directors. — To achieve human operator quality, both for the camera selection and for the automatic steering of robotic cameras, we designed an Artificial Intelligence based approach, combining several techniques, including a combination of various machine learning components to mimic the behavior of human operators.
机译:涵盖低端体育游戏的需求正在迅速增长。不幸的是,在经济上不可行的是部署我们已知用于更高级别体育赛事的传统生产方法,工作人员和设备。需要更少人员的生产方法。在过去的几年中,引入了结合回放视频混合,图形插入等的高品质单人操作设备。但是,仍然需要摄影师在运动场上操作不同的相机。 —在本文中,我们提出了一种全自动系统的概念,该系统通过一系列机器人摄像机创建多个摄像机供稿。这些机器人摄像机不是人工操作的,而是由基于人工智能的系统操纵的。该系统分析完整的运动场景以捕获相关项目,并使用该信息分别操纵不同的机器人相机以生成所需的不同相机视图。更具体地说,由AI支持的系统将不同的机器人摄像机实时指向游戏的相关部分,并应用与所需摄像机视图相对应的适当缩放比例。我们将展示应用于足球比赛的原型系统的第一个结果。 —为了进一步突破自动化生产的极限,自动摄像机操作辅以从可用摄像机进给中自动选择最有趣的摄像机角度。该自动指示可以用于创建全自动系统,也可以协助单个操作员完成完整的多机位生产。最初的实验表明,摄像机选择的质量接近真实导演的判断。 —为了在摄像头选择和机器人摄像头自动转向方面都达到人类操作员的质量,我们设计了一种基于人工智能的方法,结合了多种技术,包括各种机器学习组件的组合来模仿人类操作员的行为。

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