The Video Genome
Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel

TL;DR
This paper introduces a novel approach to video analysis by representing videos as DNA sequences, enabling efficient large-scale search, matching, and comparison inspired by genomic algorithms.
Contribution
It proposes a new method that models videos as DNA sequences and applies bioinformatics algorithms for improved video analysis tasks.
Findings
Effective video matching and comparison using DNA sequence analogy
Successful application to content-based metadata mapping
Enhanced scalability for large video databases
Abstract
Fast evolution of Internet technologies has led to an explosive growth of video data available in the public domain and created unprecedented challenges in the analysis, organization, management, and control of such content. The problems encountered in video analysis such as identifying a video in a large database (e.g. detecting pirated content in YouTube), putting together video fragments, finding similarities and common ancestry between different versions of a video, have analogous counterpart problems in genetic research and analysis of DNA and protein sequences. In this paper, we exploit the analogy between genetic sequences and videos and propose an approach to video analysis motivated by genomic research. Representing video information as video DNA sequences and applying bioinformatic algorithms allows to search, match, and compare videos in large-scale databases. We show an…
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Taxonomy
TopicsMedia Influence and Politics · Computational and Text Analysis Methods
