PARIS—For centuries, our desire to reproduce accurate, pretty images for “human consumption” has driven the advancements of camera technologies. But what if we were to change the premise and design image sensors for computers to see and analyze the information?
In that case, the fundamental data an image sensor needs to capture—and how each pixel should operate—would change completely. Further, processing would be reinvented and known algorithms would become obsolete.
Nowadays, with drones, robots and autonomous cars increasingly tasked to see their surroundings, detect obstructions and avoid collisions swiftly, these consumers of the future need an image sensor built from the ground up, specific to their computer vision.
Chronocam, a Paris-based startup, happens to have the right technology at the right time.
Two French scientists, Ryad Benosman and Christoph Posch, both well versed in neuromorphic engineering, founded Chronocam in 2014. They’ve developed an image sensor designed to capture images not based on artificially created frames, but driven by events within view.
Chronocam's two co-founders: Christoph Posch(left)and Ryad Benosman
Each pixel in Chronocam’s asynchronous time-based image sensor makes an independent decision to sample different parts of a scene at different rates. “Each pixel individually controls its sampling – with no clock involved – by reacting to light, or changes in the amount of incident light it receives,” explained Posch, Chronocam’s CTO.
Conventional image sensors capture visual information at a predetermined frame rate, Posch explained. Regardless of dynamic changes in the scene, each frame conveys information from all pixels, uniformly sampling them at the same time.
“Frame-based video acquisition is fundamentally flawed,” Chronocam CTO Posch decreed.
Shift from imaging to sensing
Pierre Cambou, Activity Leader at Yole Développement, believes fundamental changes are happening in the CMOS image sensor market. It’s shifting “toward sensing in opposition to imaging.” Cambou told EE Times, “I think Chronocam lies exactly at the forefront of this new wave of innovation that will shape the industry before the end of the decade.”
In Posch’s view, frame-based video capture is fraught with problems. It could easily miss important events that might have happened between frames. Over-sampling and under-sampling happen too often. Frame-based methodology results in redundancy in the recorded data, which triggers higher power consumption. Results include inefficient data rates and inflated storage volume. Frame-based video, at 30 or 60 frames per second, or even a much higher rate, causes “a catastrophe in image capturing,” Posch concluded.
The inspiration for Chronocam’s event-driven vision sensors comes from the two co-founders who have studied how the human eye and brain work.
Structure of biological camera (Source: Chronocam)
According to Benosman, human eyes and brains “do not record the visual information based on a series of frames.” Biology is in fact much more sophisticated. “Humans capture the stuff of interest—spatial and temporal changes—and send that information to the brain very efficiently,” he said.
Explaining Chronocam’s bio-inspired system, Benosman said, “We didn’t invent it. We observed [the nature].”
Next page: Chronocam's edge