LookOut! Interactive Camera Gimbal Controller for Filming Long Takes
Authors:
- Robert CincaRCRobert Cinca
- Enrico CostanzaECEnrico Costanza
- Gabriel BrostowGBGabriel Brostow
Preprint
Abstract
The job of a camera operator is more challenging, and potentially dangerous, when filming long moving camera shots. Broadly, the operator must keep the actors in-frame while safely navigating around obstacles, and while fulfilling an artistic vision. We propose a unified hardware and software system that distributes some of the camera operator's burden, freeing them up to focus on safety and aesthetics during a take. Our real-time system provides a solo operator with end-to-end control, so they can balance on-set responsiveness to action vs planned storyboards and framing, while looking where they're going. By default, we film without a field monitor. Our LookOut system is built around a lightweight commodity camera gimbal mechanism, with heavy modifications to the controller, which would normally just provide active stabilization. Our control algorithm reacts to speech commands, video, and a pre-made script. Specifically, our automatic monitoring of the live video feed saves the operator from distractions. In pre-production, an artist uses our GUI to design a sequence of high-level camera "behaviors." Those can be specific, based on a storyboard, or looser objectives, such as "frame both actors." Then during filming, a machine-readable script, exported from the GUI, ties together with the sensor readings to drive the gimbal. To validate our algorithm, we compared tracking strategies, interfaces, and hardware protocols, and collected impressions from a) film-makers who used all aspects of our system, and b) film-makers who watched footage filmed using LookOut.Keywords
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This publication has 14 references indexed in Scilit:
- ACT: An Autonomous Drone Cinematography System for Action Scenes2018
- Real-time planning for automated multi-view drone cinematographyACM Transactions on Graphics, 2017
- Computational video editing for dialogue-driven scenesACM Transactions on Graphics, 2017
- Fully-Convolutional Siamese Networks for Object Tracking2016
- Visual Object Tracking Performance Measures RevisitedIEEE Transactions on Image Processing, 2016
- Tracking-Learning-DetectionIEEE Transactions on Pattern Analysis and Machine Intelligence, 2011
- Creativity support tools: accelerating discovery and innovationCommunications of the ACM, 2007
- Real-Time Tracking of Moving Objects with an Active CameraReal-Time Imaging, 1998
- A new approach to visual servoing in roboticsIEEE Transactions on Robotics and Automation, 1992
- THE DISTRIBUTION OF THE FLORA IN THE ALPINE ZONE.1New Phytologist, 1912