Stargazer: An Interactive Camera Robot for Capturing How-To Videos Based on Subtle Instructor Cues
Abstract
Live and pre-recorded video tutorials are an effective means for teaching physical skills such as cooking or prototyping electronics. A dedicated cameraperson following an instructor's activities can improve production quality. However, instructors who do not have access to a cameraperson's help often have to work within the constraints of static cameras. We present Stargazer, a novel approach for assisting with tutorial content creation with a camera robot that autonomously tracks regions of interest based on instructor actions to capture dynamic shots. Instructors can adjust the camera behaviors of Stargazer with subtle cues, including gestures and speech, allowing them to fluidly integrate camera control commands into instructional activities. Our user study with six instructors, each teaching a distinct skill, showed that participants could create dynamic tutorial videos with a diverse range of subjects, camera framing, and camera angle combinations using Stargazer.
Cite
@article{arxiv.2303.03221,
title = {Stargazer: An Interactive Camera Robot for Capturing How-To Videos Based on Subtle Instructor Cues},
author = {Jiannan Li and Mauricio Sousa and Karthik Mahadevan and Bryan Wang and Paula Akemi Aoyaui and Nicole Yu and Angela Yang and Ravin Balakrishnan and Anthony Tang and Tovi Grossman},
journal= {arXiv preprint arXiv:2303.03221},
year = {2023}
}
Comments
To appear in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23), April 23--28, 2023, Hamburg, Germany