|Gaze-based Notetaking for Learning from Lecture Videos|
|Cuong Nguyen and Feng Liu|
|Computer Science Department, Portland State University|
Taking notes has been shown helpful for learning. This activity, however, is not well supported when learning from watching lecture videos. The conventional video interface does not allow users to quickly locate and annotate important content in the video as notes. Moreover, users sometimes need to manually pause the video while taking notes, which is often distracting. In this paper, we develop a gaze-based system to assist a user in notetaking while watching lecture videos. Our system has two features to support notetaking.
First, our system integrates offline video analysis and online gaze analysis
to automatically detect and recommend key content from the lecture video as
notes. Second, our system provides adaptive video playback control that
automatically reduces the video playback speed or pauses it while a user is
taking notes to minimize the user's effort in controlling video. Our study
shows that our system enables users to take notes more easily and with
better quality than the traditional video interface.
|Cuong Nguyen and Feng Liu. Gaze-based Notetaking for Learning from Lecture Videos
ACM CHI 2016. PDF
Cuong Nguyen, Wu-chi Feng, and Feng Liu. Hotspot: Making Computer Vision More Effective for Human Video Surveillance.
Information Visualization, 2016. PDF
Cuong Nguyen and Feng Liu. Making Software Tutorial Video Responsive.
ACM CHI 2015. PDF (Best Paper Honorable Mention Award)
Cuong Nguyen, Yuzhen Niu, and Feng Liu. Direct Manipulation Video Navigation on Touch Screens.
ACM MobileHCI 2014. PDF
Cuong Nguyen, Yuzhen Niu, and Feng Liu. Direct Manipulation Video Navigation in 3D.
ACM CHI 2013. PDF (Best Paper Honorable Mention Award)
Cuong Nguyen, Yuzhen Niu, and Feng Liu. Video Summagator: An Interface for Video Summarization and Navigation.
ACM CHI 2012. PDF
This video demo uses a source clip from YouTube user Bitcoin Course under a Creative Commons license. This video is narrated by Amy Burdette. This work was supported by NSF IIS-1321119 and CNS-1218589.