Neuromorphic visual object detection for enhanced driving safety

Abstract

There have been many researches on computer vision of diverse complex vision algorithms. However, despite its effectiveness, computer vision algorithm sometimes lacks the robustness of mammalian visual system for the application in dynamic environments in vehicle driving or outdoors. We have proposed that the neuromorphic visual processing algorithm based on the biological vision system is an effective approach for making detection of human objects on the road and inside the car. The effectiveness of proposed neuromorphic networks of visual processing is evaluated for the advanced driver assistance and pedestrian safety technology via the 99% of successful detection rate. The enhanced frame based neuromorphic processing showed that further applications could be sought from incorporating neuromorphic visual processing into Driver State Monitoring for the purpose of enhancing driving safety.