Smart tracking system learns to recognise faces

According to Zdenek Kalal, the Predator system can learn individual facial features, then recognise and tag the person – even from a photograph. The result is a real time tracking that improves over time. Kalal aims to create self improving real time visions that can simultaneously track, learn and detect an unknown object in a video stream. His Tracking-Learning-Detection (TLD) system – also known as Predator makes minimal assumptions about an object, the scene or the camera's motion and requires only initialisation by a bounding box while operating in real time. He has also developed a learning method that optimally combines boosting with bootstrapping and enables efficiently process of large training data sets. Using the method he built a real time multiview face detector. His PhD advisors were Krystian Mikolajczyk and Jiri Matas, while the external PhD examiner was Andrew Fitzgibbon from Microsoft Research Cambridge.