Learning user interest for image browsing on small-form-factor devices
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Gaze-based interaction for semi-automatic photo cropping
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the 15th international conference on Multimedia
Supporting region-of-interest cropping through constrained compression
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Supporting zoomable video streams with dynamic region-of-interest cropping
MMSys '10 Proceedings of the first annual ACM SIGMM conference on Multimedia systems
Adaptive encoding of zoomable video streams based on user access pattern
MMSys '11 Proceedings of the second annual ACM conference on Multimedia systems
Towards understanding user tolerance to network latency in zoomable video streaming
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Combining content-based analysis and crowdsourcing to improve user interaction with zoomable video
MM '11 Proceedings of the 19th ACM international conference on Multimedia
COZI: crowdsourced and content-based zoomable video player
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Mobile interactive region-of-interest video streaming with crowd-driven prefetching
IMMPD '11 Proceedings of the 2011 international ACM workshop on Interactive multimedia on mobile and portable devices
Adaptive encoding of zoomable video streams based on user access pattern
Image Communication
Challenges in supporting non-linear and non-continuous media access in P2P systems
Proceedings of the 20th ACM international conference on Multimedia
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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We conducted a user study with 4 video clips and 37 viewing sessions on how users interact with a web-based zoomable video system, where users can zoom and pan within the video to view selected regions-of-interest with more detail. The study shows that frequency of interaction is very high and the period during which users watch the video without interacting is comparable to the period of interaction. Users spend most of their time viewing a magnified version of the video. We also observe that their behavior is not easily predictable. Users, however, tend to be interested in common regions of the video.