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Dharmesh Tank


Video Summarization, Key Frame, Video Skimming, Image Processing.


Over the past few years, there has been a significant increase the amount of videos. Massive growth in video content poses problem of information overload and management of content. Also it made the multimedia repositories browsing, retrieval and delivery of video contents very slow and even difficult tasks. In order to manage the growing videos on the web and also to extract an efficient and valid information from the videos, more attention has to be paid towards video and image processing technologies. Video summarization has been proposed to improve faster browsing of large video collections and more efficient content indexing and access. Video summarization provide condensed and succinct representations of the content of a video stream through a combination of still images, video segments, graphical representations and textual descriptors. Video summarization methods attempt to abstract the main occurrences, scenes, or objects in a clip in order to provide an easily interpreted synopsis. The main aim of Video summarization is to provide clear analysis of video by removing duplications and extracting key frames from the video. Video Summarization is a process of creating & presenting a meaningful abstract view of entire video within a short period of time. Mainly two types of video summarization techniques are available in the literature, i.e key frame based (static video summarization) and video skimming (dynamic video summarization)[1].This paper reviews some of the recent work on video summarization information retrieval and discusses their role in current research directions which include different techniques, browsing and search paradigms, user studies, effective computing, learning, semantic queries, new features, media types, high performance indexing. Based on the current state of the art, we also discuss the major challenges for the future.

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Published in: Volume : 2, Issue : 10
Publication Date: 10/4/2016

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