School: School of Engineering
This project is a lecture browser system that helps users search a large corpus of lecture videos efficiently. This system helps the user to search the video both at the video level and segment level. A prototype system has been developed and has been hosted on our servers for testing. In addition better metadata extraction approaches have been developed. A tool has been developed based on TESSERACT and GOCR that extracts text from slides that are embedded in the lecture video. Using the extracted content from the audio and video modalities an effective approach for keyphrase extraction and lecture segmentation has been developed. The keyphrases and segments generated by this approach help summarize the content of the lecture videos and aid in better content based search and retrieval.