# Towards a Drone Cinematographer: Guiding Quadrotor Cameras using Visual Composition Principles

arXiv: https://arxiv.org/abs/1610.01691 · HTML: https://mlsanity.com/paper/1610.01691/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Oct 2016.

## Built on by (most cited first, 3 of 3)

- [Learning Camera Movement Control from Real-World Drone Videos](https://mlsanity.com/paper/2412.09620/) (2024)
- [AutoPhoto: Aesthetic Photo Capture using Reinforcement Learning](https://mlsanity.com/paper/2109.09923/) (2021)
- [Active Human Pose Estimation via an Autonomous UAV Agent](https://mlsanity.com/paper/2407.01811/) (2024)

## Abstract (arXiv)

We present a system to capture video footage of human subjects in the real world. Our system leverages a quadrotor camera to automatically capture well-composed video of two subjects. Subjects are tracked in a large-scale outdoor environment using RTK GPS and IMU sensors. Then, given the tracked state of our subjects, our system automatically computes static shots based on well-established visual composition principles and canonical shots from cinematography literature. To transition between these static shots, we calculate feasible, safe, and visually pleasing transitions using a novel real-time trajectory planning algorithm. We evaluate the performance of our tracking system, and experimentally show that RTK GPS significantly outperforms conventional GPS in capturing a variety of canonical shots. Lastly, we demonstrate our system guiding a consumer quadrotor camera autonomously capturing footage of two subjects in a variety of use cases. This is the first end-to-end system that enables people to leverage the mobility of quadrotors, as well as the knowledge of expert filmmakers, to autonomously capture high-quality footage of people in the real world.