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arXiv · 2303.03221

Stargazer: An Interactive Camera Robot for Capturing How-To Videos Based on Subtle Instructor Cues

Jiannan Li·Mauricio Sousa·Karthik Mahadevan·Bryan Wang·Paula Akemi Aoyaui·Nicole Yu·Angela Yang·Ravin Balakrishnan·Anthony Tang·Tovi Grossman
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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.

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Jiannan Li, Mauricio Sousa, Karthik Mahadevan, Bryan Wang, Paula Akemi Aoyaui, Nicole Yu, Angela Yang, Ravin Balakrishnan, Anthony Tang, Tovi Grossman. 2023-03-06. Stargazer: An Interactive Camera Robot for Capturing How-To Videos Based on Subtle Instructor Cues. https://doi.org/10.1145/3544548.3580896

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