The Video Genome

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 application for content-based metadata mapping between versions of annotated video.