The rise of Unmanned Aerial Vehicles and their increasing use in the cinema industry calls for the creation of dedicated tools. Though there is a range of techniques to automatically control drones for a variety of applications, none have considered the problem of producing cinematographic camera motion in real-time for shooting purposes. In this paper we present our approach to UAV navigation for autonomous cinematography. The contributions of this research are twofold: (i) we adapt virtual camera control techniques to UAV navigation; (ii) we introduce a drone-independent platform for high-level user interactions that integrates cinematographic knowledge. The results presented in this paper demonstrate the capacities of our tool to capture live movie scenes involving one or two moving actors.
@cite_16: Lighting plays a major role in photography. Professional photographers use elaborate installations to light their subjects and achieve sophisticated styles. However, lighting moving subjects performing dynamic tasks presents significant challenges and requires expensive manual intervention. A skilled additional assistant might be needed to reposition lights as the subject changes pose or moves, and the extra logistics significantly raises costs and time. We present a new approach to lighting dynamic subjects where an aerial robot equipped with a portable light source lights the subject to automatically achieve a desired lighting effect. We focus on rim lighting, a particularly challenging effect to achieve with dynamic subjects, and allow the photographer to specify a required rim width. Our algorithm processes the images from the photographer's camera and provides necessary motion commands to the aerial robot to achieve the desired rim width in the resulting photographs. We demonstrate a control approach that localizes the aerial robot with reference to the subject and tracks the subject to achieve the necessary motion. Our proof-of-concept results demonstrate the utility of robots in computational lighting.
@cite_12: Cameras attached to small quadrotor aircraft are rapidly becoming a ubiquitous tool for cinematographers, enabling dynamic camera movements through 3D environments. Currently, professionals use these cameras by flying quadrotors manually, a process which requires much skill and dexterity. In this paper, we investigate the needs of quadrotor cinematographers, and build a tool to support video capture using quadrotor-based camera systems. We begin by conducting semi-structured interviews with professional photographers and videographers, from which we extract a set of design principles. We present a tool based on these principles for designing and autonomously executing quadrotor-based camera shots. Our tool enables users to: (1) specify shots visually using keyframes; (2) preview the resulting shots in a virtual environment; (3) precisely control the timing of shots using easing curves; and (4) capture the resulting shots in the real world with a single button click using commercially available quadrotors. We evaluate our tool in a user study with novice and expert cinematographers. We show that our tool makes it possible for novices and experts to design compelling and challenging shots, and capture them fully autonomously.
There is currently very little literature on autonomous drones applied to cinematography. Recently, @cite_16 proposed an interesting approach to control quadrotors for lighting purposes. They present a solution to automatically achieve a specific lighting effect on dynamic subjects using a drone equipped with a fixed portable light source. Their solution processes the images from a static camera to compute the 3D motion commands for the UAV. Closer to our work, in @cite_12 , the authors address the challenge of autonomously performing camera shots with quadrotors. They present an interactive tool that allows users to design physically plausible trajectories by visually specifying shots. They use a virtual environment to compose and preview the shots. Their tool however remains limited to outdoor environment. It also requires to manually craft the path beforehand and does not allow to track targets in real-time.