Video Skimming and Characterization through the Combination of Image and Language Understanding Techniques
Michael A. Smith and Takeo Kanade, February 3, 1997, CMU-CS-97-111; School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213
Abstract
Digital video is rapidly becoming important for education, entertainment, and a host of multimedia applications. With the size of the video collections growing to thousands of hours, technology is needed to effectively browse segments in a short time without losing the content of the video. We propose a method to extract the significant audio and video information and create a “skim” video which represents a very short synopsis of the original. The goal of this work is to show ...
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