Snapstream: Snapshot-based Interaction in Live Streaming for Visual Art

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Live streaming visual art such as drawing or using design software is gaining popularity. An important aspect of live streams is the direct and real-time communication between streamers and viewers. However, currently available text-based interaction limits the expressiveness of viewers as well as streamers, especially when they refer to specific moments or objects in the stream. To investigate the feasibility of using snapshots of streamed content as a way to enhance streamer-viewer interaction, we introduce Snapstream, a system that allows users to take snapshots of the live stream, annotate them, and share the annotated snapshots in the chat. Streamers can also verbally reference a specific snapshot during streaming to respond to viewers' questions or comments. Results from live deployments show that participants communicate more expressively and clearly with increased engagement using Snapstream. Participants used snapshots to reference part of the artwork, give suggestions on it, make fun images or memes, and log intermediate milestones. Our findings suggest that visual interaction enables richer experiences in live streaming.
Publisher
Association for Computing Machinery
Issue Date
2020-04-27
Language
English
Citation

2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020

DOI
10.1145/3313831.3376390
URI
http://hdl.handle.net/10203/277569
Appears in Collection
CS-Conference Papers(학술회의논문)
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