Real-Time Pupil-Tracking embedded-system based on neural networks

This paper proposes a low-cost video-based Real-Time Pupil-Tracking embedded system which will allow people with reduced mobility to control a wheelchair through their eyes. The main aspect of the method is its capacity to be implemented in a portable computing system, reduced both in computing power and in RAM memory. The Pupil-Tracking system is based on Feedforward Neural Networks-using offline training-, and in the “dark pupil effect”. The performance of the method was validated using an own database, built under different ambient lighting conditions.