Media Streams: an iconic visual language for video representation
Human-computer interaction
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Video summarization based on user log enhanced link analysis
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Toward emergent representations for video
Proceedings of the 13th annual ACM international conference on Multimedia
Tweet the debates: understanding community annotation of uncollected sources
WSM '09 Proceedings of the first SIGMM workshop on Social media
SocialSkip: pragmatic understanding within web video
Proceddings of the 9th international interactive conference on Interactive television
Editing by Viewing: Automatic Home Video Summarization by Viewing Behavior Analysis
IEEE Transactions on Multimedia
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Every second millions of users enjoy content streaming on diverse video players (e.g., Web, Apps, social networks) and create billions of interactions within online video, such as play, pause, seek/scrub. This collective intelligence of video viewers might be leveraged into useful information for improved video navigation. For example, we can accurately detect and retrieve interesting scenes through the analysis of the aggregated users' replay interactions with the video player. Effective crowdsourcing of video interactions is grounded on previous work in multimedia, user modeling, and controlled user experiments. These research issues are described for the case of user-based detection of video thumbnails that stand for the semantics of the video. Moreover, we demonstrate the respective experimental environment with a focus on educational and user generated (e.g., how-to, lecture) videos.