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A partnership between two Dunedin-based heavyweights could have "huge" commercial potential, its backers say.
The University of Otago and NHNZ Moving Images have signed a research agreement, with the aim to develop a cutting-edge image recognition system, similar to those used by law enforcement agencies.
Under the project, researchers from the university's information science department will gain access to the television production company's archive of more than 200,000 hours of footage.
Dr Jeremiah Deng said with the help of new technology it was possible to identify objects in each shot, a huge boon to those searching archival footage.
Aside from the commercial potential for those searching archived footage, there was also consumer potential for home users searching their computers, he said.
"The commercial potential is huge," NHNZ emerging media manager Caroline Cook said.
At present, each shot filmed in the field comes back to NHNZ, or other production companies, needing to be recorded, with such things as the action, main objects and camera angles listed on a shot list.
"This is a painstaking and laborious and very necessary job, as the writers and directors use these 'shot lists' to create the first rough cut of the production."
That process was labour-intensive and a costly component of production, but an image recognition system could deliver the right footage in minutes as opposed to days.
"Whoever developed this type of system has the potential to sell it to other production companies," she said.
Another potential for the image recognition system, which has been used by law enforcement agencies to detect people in crowds, was finding the right shots from archived footage that has not been categorised in any way.
"If we could get a system which can search for recognisable images that haven't been shot-listed, this would help footage archivists immensely."
Dr Deng said the NHNZ archive was a "gold mine" for the research team, which was hoping to secure funding for the project.
The research team will soon have a delivery of a large data set of wildlife clips for recognition experiments, on such popular animals as elephants, zebras, lions and polar bears.