Artificial intelligence combined with a novel bio-inspired camera achieves 100 times faster detection of pedestrians and obstacles than current automotive cameras.

Event cameras are a recent innovation based on a different principle. Instead of a constant frame rate, they have smart pixels that record information every time they detect fast movements. Gehrig and Scaramuzza came up with a hybrid system that combines the best of both worlds: It includes a standard camera that collects 20 images per second, a relatively low frame rate compared to the ones currently in use. Its images are processed by an AI system, called a convolutional neural network, that is trained to recognize cars or pedestrians. The data from the event camera is coupled to a different type of AI system, called an asynchronous graph neural network, which is particularly apt for analyzing 3-D data that change over time. Detections from the event camera are used to anticipate detections by the standard camera and also boost its performance. The result is a visual detector that can detect objects just as quickly as a standard camera taking 5,000 images per second would do but requires the same bandwidth as a standard 50-frame-per-second camera.

Source: ScienceDaily