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Indexed Captioned Searchable Videos

This presentation by Cecilia Y. Chen from the University of Houston explores the integration of video in online coursework. It highlights the widespread use of platforms like MIT OpenCourseware and YouTube Edu, and discusses the advantages and challenges of video lectures, particularly focusing on their accessibility. The presentation examines indexing methods that allow for segmented and searchable videos, using both image and text-based approaches to identify transition points for easier navigation. This enhances the learning experience by facilitating quick access to relevant content.

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Indexed Captioned Searchable Videos

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  1. Indexed Captioned Searchable Videos Cecilia Y. Chen University of Houston July 11,2012

  2. Introduction • Usage of video to deliver coursework online: commonplace • Evidence for video usage: - MIT OpenCourseware , - Apple’s iTunes University - YouTube Edu

  3. Classroom lecture videos widely used at University of Houston • Tablet PC recordings

  4. Survey focus group: • Video lectures : powerful and versatile resource • The biggest weakness of the video format : Inability to quickly access the content of interest

  5. ICS Videos • Indexing: Segmented videos • Search: Keyword search in video • Captioning: Scrolling text for audio • Integrated in ICS Video Player • Project Goal: Quick access to video content

  6. Indexing: Finding Transition Points • Indexing : dividing video into segments; • User can start playback from any index frame • Transition Point: is a frame that has changes significantly when compared to another frame.

  7. Image approach: comparing images by pixel to find transition points • Text approach: comparing images using text to find transition points using OCR(Optical Character Recognition)

  8. Image approach vs Text approach

  9. Preliminary Results • There are special cases that is a lot faster to use the text approach • When a video is processed with text comparison at the end the difference in time to process might not be that significant • Most of the time the text comparison will recognize transition points accurately

  10. Resources • Houston, University of. Indexed Captioned Searchable Videos for STEM Courseware. 2009. <http://icsvideos.cs.uh.edu/>. • Tuna T, Subhlok J, Barker L,Shah S, Varghese V, Johnson O. "Development and Evaluation of Indexed Captioned ." (n.d.). • Tuna T, Subhlok J, Shah S. "Indexing and Keyword Search to Ease Navigation ." (n.d.).

  11. Questions

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