This lecture overviews Video Summarization that has many applications in video description, search, retrieval and browsing. It covers the following topics in detail: Video Summarization Models: a) Static video summary (storyboard), Video Captioning, Key framing extraction, b) Dynamic video summarization (skimming). Video Summarization Techniques (Video Summarization with Global and Local Features, Scene identification with global features, Keyframe selection with local features. Event-based video summarization. Motion and Color Based video Summarization. Object-Based video summarization. Attention-based video summarization. Clustering-based Video summarization. Selection of shot / shot boundaries-based video summarization. Trajectory-based Video Summarization). Supervised learning for Video Summarization. Unsupervised learning for Video Summarization. Video Summarization with Neural Networks (NN). Video Summarization Applications.
