SynTag: A Web-based Platform for Labeling Real-time Video (ACM CSCW 2012 Short Paper)

Real-time video streaming has been widely used in multimedia learning environments. As production of online videos is increasing exponentially, it is becoming more difficult for users to reach relevant content. In this paper, we propose SynTag, a web-based platform that enables users to label three types of tags—Good, Question, and Disagree—and to make comments synchronously and asynchronously with visualization of time-stamp video previews on an interactive timeline. SynTag generates real-time thumbnails by using real-time tags for presenters to receive instant feedback and for other users to retrieve presentation videos. In a pilot study, we found our users’ tagging behaviors significantly different when they were in lecture events or discussion events. We envision that enabling users to apply tags in real-time will help reduce the complexity of classification of videos.

Publication

Yen-Chia Hsu, Tay-Sheng Jeng, Yang-Ting Shen, and Po-Chun Chen. 2012. SynTag: A Web-based Platform for Labeling Real-time Video. In Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work (CSCW ’12). ACM

For citation, please visit the ACM link of this paper.

Yang-Ting Shen, Tay-Sheng Jeng, Yen-Chia Hsu. 2011. A “Live” Interactive Tagging Interface for Collaborative Learning. In: Luo Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2011. Lecture Notes in Computer Science, vol 6874. Springer, Berlin, Heidelberg

GitHub

https://github.com/legenddolphin/SynTag

Related Materials

Interpretecture – iStudio Demonstration Video
(The video is directed by Yang-Ting Shen, IA lab, National Cheng Kung University, Taiwan)
Interpretecture – A Space Interpreter
A “live” interactive tagging interface for collaborative learning

SynTag System

1. Archiving Service

22

2. Recording, Broadcasting, and Tagging Service

11

Project Advisor

Prof. Tay-Sheng Jeng

Acknowledgements

Thanks to amcharts‘ free version Flex charts API.
Thanks to all group members and Prof. Tay-Sheng Jeng.
Thanks to Jackie Chia-Hsun Lee‘s research method suggestions.

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