DNA techniques could help facial recognition evolve
23 October 2017 17:01 GMT

Recent research suggests video analysis software could be dramatically improved thanks to software advances in DNA sequence analysis. 

Experts say that treating video as a scene that evolves in the same way DNA does, software tools and techniques could transform automated visual surveillance.

Writing in the Conversation, Jean-Christophe Nebel, Associate Professor in Pattern Recognition, Kingston University, writes that we need software that can deal with this variability rather than treating it as an inconvenience – a fundamental change.

"And one area that is used to dealing with large amounts of very variable data is genomics".He calls it “vide-omics”. 

He adds that his research group at Kingston University has, for the first time, shown that videos could be analysed even when captured by a freely moving camera. By identifying camera motion as mutations, they can be compensated so that a scene appears as if filmed by a fixed camera.

Genomic analysis includes the study of the evolution of genes over time by investigating the mutations which have occurred. This is surprisingly similar to the challenge in visual surveillance, which relies on interpreting the evolution of a scene over time to detect and track moving pedestrians. By treating differences between the images that make up a video as mutations, we can apply the techniques developed for genomic analysis to video.