Abstract
Autonomous aerial cinematography has the potential to enable automatic capture of aesthetically pleasing videos without requiring human intervention, empowering individuals with the capability of high-end film studios. Current approaches either only handle off-line trajectory generation, or offer strategies that reason over short time horizons and simplistic representations for obstacles, which result in jerky movement and low real-life applicability. In this work we develop a method for aerial filming that is able to trade off shot smoothness, occlusion, and cinematography guidelines in a principled manner, even under noisy actor predictions. We present a novel algorithm for real-time covariant gradient descent that we use to efficiently find the desired trajectories by optimizing a set of cost functions. Experimental results show that our approach creates attractive shots, avoiding obstacles and occlusion 65 times over 1.25 hours of flight time, re-planning at 5 Hz with a 10 s time horizon. We robustly film human actors, cars and bicycles performing different motion among obstacles, using various shot types.
Abstract (translated)
自主航拍摄影技术有可能在不需要人工干预的情况下自动捕捉美观的视频，使个人具备高端电影制片厂的能力。当前的方法要么仅处理离线轨迹生成，要么提供在短时间范围内推理的策略和对障碍物的简单表示，这导致不稳定的运动和低的实际适用性。在这项工作中，我们开发了一种空中拍摄方法，即使在嘈杂的演员预测下，也能够以原则的方式权衡镜头平滑度，遮挡和电影摄影指南。我们提出了一种用于实时协变梯度下降的新算法，我们通过优化一组成本函数来有效地找到所需的轨迹。实验结果表明，我们的方法创造了有吸引力的镜头，在1.25小时的飞行时间内避开了障碍物和遮挡65次，在5秒时重新规划了10秒的时间范围。我们使用各种镜头类型，强有力地拍摄人类演员，汽车和自行车在障碍物之间进行不同运动。
URL
https://arxiv.org/abs/1808.09563
