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We present a system that assists users in viewing videos of lectures on small screen devices, such as cell phones. It automatically identifies semantic units on the slides, such as bullets, groups of bullets, and images. As the participant views the lecture, the system magnifies the appropriate semantic unit while it is the focus of the discussion. The(More)
We present a context-aware system that simultaneously increases energy-efficiency and readability for educational videos on smart-phones with OLED displays. Our system analyzes the content of each frame of the video and intelligently modifies the colors and presentations of specific regions of the frame to drastically reduce display energy consumption while(More)
As members of the Dissertation Committee, we certify that we have read the dis-sertation prepared by Qiyam Junn Tung entitled Who Moved My Slide? Recognizing Entities in a Lecture Video and Its Applications and recommend that it be accepted as fulfilling the dissertation requirement for the Degree of Doctor of Philosophy. Final approval and acceptance of(More)
A significant part of many videos of lectures is presentation slides that occupy much of the field of view. Further, for a student studying the lecture, having the slides sharply displayed is especially important, compared with the speaker, background, and audience. However, even if the original capture supports it, the bandwidth required for real time(More)
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