@article{905,
  author = {Haojin Yang, Harald Sack, Christoph Meinel},
  title = {Lecture Video Indexing and Analysis Using Video OCR Technology},
  journal = {Journal of Multimedia Processing and Technologies},
  year = {2011},
  volume = {2},
  number = {4},
  doi = {},
  url = {http://www.dline.info/jmpt/fulltext/v2n4/2.pdf},
  abstract = {Texts displayed in lecture videos are closely related to the lecture content. Therefore, they provide a valuablesource for indexing and retrieving lecture videos. Textual content can be detected, extracted and analyzed automatically byvideo OCR (Optical Character Recognition) techniques. In this paper, we present an approach for automated lecture videoindexing based on video OCR technology: first, we developed a novel video segmenter for the structure analysis of slidevideos. Having adopted a localization and verification scheme, we perform text detection secondly. We apply SWT (StrokeWidth Transform) not only to remove false alarms from the text detection stage, but also to analyze the slide structure further.To recognize texts, a multi-hypotheses framework is applied, that consists of multiple text binarization, OCR, spell checkingand result merging processes. Finally, we have implemented a novel algorithm for extracting lecture structure from the OCR-transcript by using geometrical information and text stroke width of detected text lines. We use both segmented key framesand extracted lecture outlines for the further video indexing. The accuracy of the proposed approach is proven by evaluation.},
}