Watching a large number of video clips captured by professional filmmakers is an effective way for beginners to learn video shooting skills and ultimately derive their own creative works. Therefore, we designed an imitation-based system that learns the artistic intention of the cameramen through watching professional aerial videos. We designed a camera planner that analyzes the video contents and previous camera motion to predict future camera motion. Furthermore, we propose a planning framework, which can imitate a filming style by "seeing" only one single demonstration video of such style. We named it "one-shot imitation filming." To the best of our knowledge, this is the first work that extends imitation learning to autonomous filming. Experimental results in both simulation
and field test exhibit significant improvements over existing techniques and our approach
managed to help inexperienced pilots capture cinematic videos.

The heuristic-based method is to employ heuristic aesthetic objectives to automate filming. we designed an Autonomous CinemaTography system "ACT" by proposing a viewpoint quality metric focusing on the visibility of the 3D human skeleton of the subject. We expanded the application of human motion analysis and simplified manual control by assisting viewpoint selection using a through-the-lens method.