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Research Projects

SLIC (Semantically Linked Instructional Content)

The SLIC (Semantically Linked Instructional Content) project aims to assist students and scholars to efficiently browse and seek segments of interest in educational videos of lectures and talks. In particular, it focuses on lectures that use slides, where the content of the slides file gives valuable hints as to how to break the video into meaningful parts (segments), and how to enable students to access these segments. In this way, a student who is seeking a specific topic in the video of a lecture(s) can first find the relevant slide(s), and start watching the video only from the segment(s) where this slide was used. Using similar ideas, the system has the potential to improve significantly the understandability of the video, improve its quality, and increase the overall effectiveness of the learning process. Additionally, the system has promise for assisting students with disabilities and bilingual students to access the video.

synchronize We have developed a fully automatic and robust slide-to-video matching algorithm that can handle a variety of different videos captured by one or multiple PTZ cameras. Our approach applies SIFT keypoints to match frames to slides under constraint homography by using RANSAC. A multi-phase algorithm was proposed for gaining both high accuracy and efficiency. To further improve accuracy, we integrate the visual features with temporal information and camera cues into dynamic Hidden Markov models to find an optimal slide sequence for the frame sequence.

More details about the project and a demo. can be found on the project webpage.

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