CineMPC: Controlling Camera Intrinsics and Extrinsics for Autonomous Cinematography
This work addresses the problem of autonomous cinematography for UAV operators by enabling full camera control, though it is incremental as it builds on existing MPC methods by adding intrinsic parameter control.
The authors tackled autonomous cinematography by controlling both camera position/orientation and intrinsic parameters like focal length, enabling rich cinematographic effects such as focus and depth perception. Their CineMPC algorithm successfully achieved a full array of these effects in photo-realistic experiments.
We present CineMPC, an algorithm to autonomously control a UAV-borne video camera in a nonlinear Model Predicted Control (MPC) loop. CineMPC controls both the position and orientation of the camera -- the camera extrinsics -- as well as the lens focal length, focal distance, and aperture -- the camera intrinsics. While some existing solutions autonomously control the position and orientation of the camera, no existing solutions also control the intrinsic parameters, which are essential tools for rich cinematographic expression. The intrinsic parameters control the parts of the scene that are focused or blurred, the viewers' perception of depth in the scene and the position of the targets in the image. CineMPC closes the loop from camera images to UAV trajectory and lens parameters in order to follow the desired relative trajectory and image composition as the targets move through the scene. Experiments using a photo-realistic environment demonstrate the capabilities of the proposed control framework to successfully achieve a full array of cinematographic effects not possible without full camera control.