Imperial College London


Faculty of EngineeringDepartment of Computing

Chair in Machine Learning and Pattern Recognition



m.bronstein Website




569Huxley BuildingSouth Kensington Campus






BibTex format

author = {Bronstein, AM and Bronstein, MM and Kimmel, R},
title = {The Video Genome},
url = {},

RIS format (EndNote, RefMan)

AB - Fast evolution of Internet technologies has led to an explosive growth ofvideo data available in the public domain and created unprecedented challengesin the analysis, organization, management, and control of such content. Theproblems encountered in video analysis such as identifying a video in a largedatabase (e.g. detecting pirated content in YouTube), putting together videofragments, finding similarities and common ancestry between different versionsof a video, have analogous counterpart problems in genetic research andanalysis of DNA and protein sequences. In this paper, we exploit the analogybetween genetic sequences and videos and propose an approach to video analysismotivated by genomic research. Representing video information as video DNAsequences and applying bioinformatic algorithms allows to search, match, andcompare videos in large-scale databases. We show an application forcontent-based metadata mapping between versions of annotated video.
AU - Bronstein,AM
AU - Bronstein,MM
AU - Kimmel,R
TI - The Video Genome
UR -
ER -