Cameras have slowly made their way into the portable gadgets we all carry around with us and not having a camera in a new device is viewed as a missing feature. It’s got to the point now where the latest smartphones even have two cameras so as to make for better video chat. But while the prevalence and quality of the cameras has gone up, the software still lags behind in terms of being able to identify and track objects in any real-time or captured footage.
That is about to change due to the work of Czech student Zdeneki Kalai. Working on his Ph.D at the University of Surrey he has created a new visual object tracking algorithm called Predator that blows away everything that has come before it in the consumer-space at least.
This algorithm not only tracks, it learns the more it gets used. As the video above demonstrates it can pick up new objects on the fly, keep up with movement by tracking in real-time, handles object moving out of view and reappearing very well, and can even identify copies of an object in images shown on the camera being monitored.
Kalai believes what he has created, a combination of tracking, learning, and detection is completely unique and allows for a whole new set of functionality to be applied when looking at video feeds.
In the video he gives examples of a new interface that can detect your fingers and use them to draw, learning to get better at trakcing those fingers as it is used more. Face recognition can be enhanced so you can show the camera pictures of suspected thieves so it can watch and detect them as they enter a store without the need of a human monitoring the video too. It could also improve visual search, help with image stabilization when looking at a specific object, and track handwriting.
There’s a further nine videos showing Predator in action and how it learns over at Kalai’s YouTube channel. We wouldn’t be surprised if Google, Apple, and Microsoft have already been in touch with him showing an interest.
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