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Implementation of Content Based Lecture Video Retrieval By Text

Authors(4):

Prashant Zanjugade, Neha Shinde, Omkar Devle, Darshana Gandre
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E-Teaching is becoming popular nowadays, as a result of this there is huge increase in the amount of lecture video data on the World Wide Web. Lecture videos contain text information in the visual channels: the presentation slides and lecturer's speech. Therefore, a more effective method for retrieval of video within large lecture video archives is needed. So, in this paper we present an approach for automated video indexing and searching of video in archives. Firstly, we apply automatic video segmentation which will fragment the video into number of frames and then key-frame detection is applied to offer a visual guideline for the video content navigation. Subsequently, by applying video Optical Character Recognition (OCR) technology on key-frames we extract textual metadata. The OCR detects as well as transcripts slide text for keyword extraction, by which all keywords are extracted from video for content based video browsing and search.

Prashant Zanjugade, Neha Shinde, Omkar Devle, Darshana Gandre

Lecture videos, Video Segmentation, Optical Character Recognition (OCR), Keyframe detection, Indexing, Ranking.

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Publication Details

Published in : Volume 3 | Issue 3 | May-June - 2017
Date of Publication Print ISSN Online ISSN
2017-06-30 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
140-144 IJSRSET173326   Technoscience Academy

Cite This Article

Prashant Zanjugade, Neha Shinde, Omkar Devle, Darshana Gandre, "Implementation of Content Based Lecture Video Retrieval By Text", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 3, pp.140-144, May-June-2017.
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