Lecture Video Indexing and Analysis Using Video OCR Technology

The text displayed in a lecture video is closely related to the lecture content. Therefore, it provides a valuable source for indexing and retrieving lecture video contents. Textual content can be detected, extracted and analyzed automatically by video OCR (Optical Character Recognition) techniques. In this paper, we present an approach for automated lecture video indexing based on video OCR technology: Firstly, we developed a novel video segmenter for an automated slide video structure analysis. Having adopted a localization and verification scheme, we perform text detection secondly. We employ SWT (stroke width transform) not only to remove false alarms from the text detection, but also to analyze the slide structure further. To recognize texts, a multi-hypotheses framework is adopted, that consists of multiple text segments, OCR, spell checking and result merging processes. Finally, we implemented a novel algorithm for slide structure analysis and extraction by using the geometrical information of detected text lines. The accuracy of the proposed approach is proven by evaluation.