Prophesee - Retinal Event-Based Neuromorphic Vision

The human retina does not transmit raw pixel values to the brain; instead, it performs dramatic data compression on-sensor. Photoreceptors detect light, but retinal ganglion cells—the retina's output neurons—only fire when light intensity changes rapidly. Stationary scenes generate almost zero neural activity; motion, flicker, and edges trigger spike bursts. This event-driven encoding reduces the optic nerve's data burden to approximately 1 Mbps despite observing a complex visual scene—a 1000-fold compression versus a conventional 1 gigapixel video stream. Prophesee engineered silicon chips replicating this retinal principle: thousands of pixels, each with its own photodiode and change-detection circuitry. When light intensity changes above a threshold, that pixel emits a time-stamped event; unchanged regions remain silent. These event cameras require minimal power, generate vast data reductions, and excel at motion detection and low-light vision where conventional cameras fail. Applications range from industrial robotics (tracking fast-moving objects at microsecond precision) to autonomous vehicles (robust edge detection and motion segmentation) to surveillance (detecting rare, meaningful events in hours of static footage). By mirroring retinal compression architecture, Prophesee achieved sensor performance impossible with conventional frame-based approaches.