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Artificial intelligence (AI) 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 achieved by researchers of the University of Zurich can greatly improve the safety of automotive systems and self-driving cars. The system developed by Daniel Gehrig and Davide Scaramuzza from the University of Zurich uses a hybrid approach combining a standard camera and an event camera with AI to detect obstacles around a car much quicker and with less computational power.
The bio-inspired camera system is designed to address the challenge of quick detection of pedestrians and obstacles, crucial for driver safety. By combining the best features of frame-based cameras and event cameras with AI systems, the researchers have created a visual detector that can detect objects as quickly as a camera taking 5,000 images per second but with the bandwidth requirement of a standard 50-frame-per-second camera. The system leads to one hundred times faster detections while reducing data transmission and computational power needed.
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