Video Summarization using Keyframe Extraction and Video Skimming
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Video is one of the robust sources of information and the consumption of online and offline videos has reached an unprecedented level in the last few years. A fundamental challenge of extracting information from videos is a viewer has to go through the complete video to understand the context, as opposed to an image where the viewer can extract information from a single frame. In this work, we attempt to employ different Algorithmic methodologies including local features and deep neural networks along with multiple clustering methods to find an effective way of summarizing a video by interesting keyframe extraction.
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