engleski

Automatic Video Editor for Reportages Assisted by Unsupervised Machine Learning

In this paper we explain the methodology for making a computer program that will automatically edit videos with the only input being files containing raw video interviews. Program produces two files as its outputs – an MP4 video file and an XML file compatible with the most popular video editing programs. MP4 video file will be the edited video program made and the XML file will contain the timeline information which the program puts together with clip durations, in and out points on the timeline, and information about the timeline itself. Such a program is useful for two general types of users. The first group would be video editors for whom it would save time - upon generating the XML they could continue improving the cut, without wasting time manually cutting and sorting clips. The second type of users that could benefit using this program are people who are not professional video editors and would use this program as a simple tool that enables them to quickly edit the interviews they shot and publish them on the web. In processing the inputted video files, among other technologies, program uses unsupervised machine learning. The program is written in Python and uses FFmpeg for converting audio and video files. The program has been tested on a limited sample of video interviews carried out in English.

Automatic video editing ; Topic modeling ; Unsupervised machine learning ; Video reportages ; Documentary

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