  Real-time tracking is an important problem in computer vision in which most
methods are based on the conventional cameras. Neuromorphic vision is a concept
defined by incorporating neuromorphic vision sensors such as silicon retinas in
vision processing system. With the development of the silicon technology,
asynchronous event-based silicon retinas that mimic neuro-biological
architectures has been developed in recent years. In this work, we combine the
vision tracking algorithm of computer vision with the information encoding
mechanism of event-based sensors which is inspired from the neural rate coding
mechanism. The real-time tracking of single object with the advantage of high
speed of 100 time bins per second is successfully realized. Our method
demonstrates that the computer vision methods could be used for the
neuromorphic vision processing and we can realize fast real-time tracking using
neuromorphic vision sensors compare to the conventional camera.
