How facial recognition can unlock video archive value

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Kablamo’s co-CEO, Angus Dorney, recently spoke to ComputerWorld about how facial recognition and AI can unlock tremendous amounts of value in video archives. Read the full story here. An excerpt is below.

Archive value

The capability also has enterprise applications – particularly for media organisations wanting to find relevant footage or stills in their video archives.

“They have millions of hours of video content and its typically stored in multiple legacy systems, there is no or varying meta-tagging, and the search processes for finding content are extremely old and they’re manual and they cut across multiple systems,” explains Angus Dorney, co-CEO of Sydney and Melbourne-based cloud technology firm Kablamo.

“If you’re a newsmaker in a media organisation or work for a government archive and somebody asks you for a specific piece of footage it’s very difficult and time consuming and expensive to try and find,” he adds.

Kablamo builds solutions that have a “YouTube-like user experience” to find relevant archive footage. Using AWS face and object recognition tools, users simply type in a person or thing “and get a list back of prioritised rankings, where it is, and be able to click and access that example right away,” Dorney – a former Rackspace general manager – says.

The machine learning models behind the capability, over time, can refine and adjust their behaviour, making results more accurate and more useful to users.

“You really have a computer starting to function like a human brain around these things which is incredibly exciting,” Dorney adds.