arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1808.09563cs.ROcs.AI

Autonomous drone cinematographer: Using artistic principles to create smooth, safe, occlusion-free trajectories for aerial filming

Carnegie Mellon University(卡内基梅隆大学);Yamaha Motor Co., Ltd.(雅马哈发动机株式会社)

Rogerio Bonatti, Yanfu Zhang, Sanjiban Choudhury, Wenshan Wang, Sebastian Scherer

英文摘要:

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.

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。

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