Content-based Lecture Video Indexing Martin Halvorsen
Content-based Lecture Video Indexing Content Introduction Research Questions Background Proposed System Implementations Conclusions
Content-based Lecture Video Indexing IntroductionIntroduction
Introduction Blackboard presentations considered as essential and indispensable Hard to navigate through traditional videos Lack of expertise and time consuming
Content-based Lecture Video Indexing Research questions
Content-based Lecture Video Indexing Research questions Q1: How can foreground/background segmentation in a lecture video work for different writing-boards?
Content-based Lecture Video Indexing Research questions Q2: How to automatically extract meta-data from lecture videos?
Content-based Lecture Video Indexing Research questions Q3: How to use such meta-data for indexing and searching of lecture videos?
Content-based Lecture Video Indexing BackgroundBackground
Background Tracking, detection and separation algortihms Motion estimation, background models, statistical estimated models
Content-based Lecture Video Indexing Background Eirik Grythe – segmentation and text detection Synne Repp – simulated indexing alg.
Content-based Lecture Video Indexing Proposed System
Content-based Lecture Video Indexing Proposed system Superior blockdiagram of the proposed system Blackboard extractionMetadata ExtractionIndex GenerationF/B Segmentation
Content-based Lecture Video Indexing Teacher segmentation
Content-based Lecture Video Indexing Teacher segmentation Motion estimation - SAD
Content-based Lecture Video Indexing Teacher segmentation Morphological operations to close holes in the detection
Content-based Lecture Video Indexing Teacher segmentation Using motion history to improve the segmentation algorithm
Content-based Lecture Video Indexing Teacher segmentation Replace blocks that has motion in it
Content-based Lecture Video Indexing Teacher segmentation Demonstration
Content-based Lecture Video Indexing Meta-data extraction
Content-based Lecture Video Indexing Meta-data extraction What is meta-data? How to extract blackboard content? Statistics
Content-based Lecture Video Indexing Meta-data extraction Demonstration
Content-based Lecture Video Indexing IndexingIndexing
Indexing When to extract an image? Search a lecture video using extracted features
Content-based Lecture Video Indexing ConclusionsConclusions
Conclusions Adaptive segmentation possible by using motion estimation Extraction of content is possible using image difference Meta-data is possible to extract using a foreground model to compare against new content Statistics of extracted meta-data can be used to automatically index a lecture video
Content-based Lecture Video Indexing The end