Bio-Inspired Camera

Artificial intelligence combined with a novel bio-inspired camera achieves 100 times faster detection of pedestrians and obstacles than current automotive cameras. This important step for computer vision and AI and can greatly improve the safety of automotive systems and self-driving cars

 Daniel Gehrig and Davide Scaramuzza from the Department of Informatics at the University of Zurich (UZH) have combined a novel bio-inspired camera with AI to develop a system that can detect obstacles around a car much quicker than current systems and using less computational power.

Most current cameras are frame-based, meaning they take snapshots at regular intervals. Those currently used for driver assistance on cars typically capture 30 to 50 frames per second and an artificial neural network can be trained to recognize objects in their images — pedestrians, bikes, and other cars.