A Survey on Content Based Lecture Video Retrieval Using Speech and Video Text Information

Recording lectures and putting them on the Web for access by students has become a general trend at various universities. The amount of lecture video data is growing rapidly on the World Wide Web (WWW). Lecture videos contain text information in the visual as well as audio channels: the presentation slides and lecturer's speech. So it becomes a need for an efficient method for video retrieval in WWW or within large lecture video archives. To extract the visual information, we apply video content analysis to detect slides and (OCR) Optical Character Recognition to obtain their text and (ASR) Automatic Speech Recognition is used to extract spoken text from the recorded audio. In this paper we present an approach for automated video indexing and video search in large lecture video archives. Firstly we apply automatic video segmentation and key-frame detection. Then; we apply video Optical Character Recognition (OCR) technology on key-frames to extract textual metadata and Automatic Speech Recognition (ASR) on lecture audio tracks.