Video Skimming for Quick Browsing based on Audio and Image Characterization
Abstract
Digital video is rapidly becoming an important source for information, entertainment and a host of multimedia applications. With the size of these 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 short synopsis of the original. The extraction of significant information, such as specific objects, audio keywords and relevant video structure, is made possible through the integration of techniques in image and language understanding. The resulting skim is much smaller, and retains the essential content of the original segment.
BibTeX
@techreport{Smith-1995-13928,author = {Michael Smith and Takeo Kanade},
title = {Video Skimming for Quick Browsing based on Audio and Image Characterization},
year = {1995},
month = {July},
institute = {Carnegie Mellon University},
address = {Pittsburgh, PA},
number = {CMU-CS-95-186},
}