Event-oriented CMOS image sensor will be used for lidar

According to reports, in the rapidly growing market of factory automation, the Internet of Things, and self-driving vehicles, CMOS image sensors seem to play a role no longer as human consumer products, but as sensors that allow machines to acquire data and make them understand the world.

Pierre Cambou, head of the MEMS & Imaging Department at Yole, a well-known French market research and technical analysis agency, commented: “The sensing capabilities of CMOS image sensors will gradually exceed their own imaging capabilities,” and bold predictions “by 2030, half CMOS image sensors will serve the field of perception."

Prophesee SA (formerly Chronocam), headquartered in Paris, France, is a revolutionary leader. As an advanced neuro-vision system design company, an event-based method was proposed for sensing and processing. Prophesee's bionic vision technology has always been considered to be substantially different from traditional machine vision and is in a dangerous "premature period." Luca Verre, co-founder and CEO of Prophesee, told us: "In the near future, this idea will prove to be wrong."

In a face-to-face interview with Luca Verre, we learned that Prophesee has obtained a B+ round of financing (in the past three years, Prophesee has raised $40 million in funds). Prophesee has signed a cooperation agreement with a large consumer electronics company (without revealing a specific name). Most importantly, Prophesee is actively leaping out of the usual technical concepts into a reference system for developers.

Prophesee's first reference design is for VGA resolution applications. Prophesee provides asynchronous time-based image sensors (ATIS) chips and software algorithms. The ASIC will be manufactured by Israel's foundry partners (our guess is probably Tower Jazz).

Prophesee is temporarily reluctant to provide a detailed description of the ASIC and reference design specifications. It is planned to officially release this product in the coming weeks. Despite this, the reference design can provide system designers with the opportunity to witness and experience the role of ATIS in the field of data sensing, and it has been proven that the start-up company is a milestone. ATIS features high instantaneous resolution, low data rate, high dynamic range, and low power consumption.

Camera = bottleneck

Manufacturers of machine vision systems, whether they are smart factories, the Internet of Things, or self-driving vehicles, have already focused on event-based methods. This was strongly promoted by Prophesee co-founders Ryad Benosman and Christoph Posch.

Can capture all the detailed visual information that the traditional camera obtains, Verre thinks "the camera becomes the technological bottleneck". There is no doubt that the camera is the most powerful sensor device. However, the camera's processing speed may slow down for the visual data of automated systems, surveillance cameras, or highly automated vehicles.

But when it comes to autopilot, Verre thinks that the central processing system inside the vehicle is “bombed” by data from cameras, laser radars, radars, and other visual sources. The key to managing this type of overload is how best to reduce the amount of raw data from the sensor. Sensors can only capture data and bring extra unwanted visual information.

Prophesee explained to the reporter that Prophesee's event-driven vision sensor was inspired by biology. This view stems from the co-founder's study of human eyes and brain work. Ryad Benosman, one of Prophesee’s founders, told us that human eyes and brain “do not record visual information based on a series of frames”. Creatures are more complex than you think. "Humans will capture what is interested in spatio-temporal changes and send this information to the brain effectively." This is also the main role of the ATIS of Prophesee.

In short, Prophesee's ATIS provides everything that frame-based image sensing can't do. According to another co-founder, Christoph Posch, "a frame-based approach leads to redundant recording of data, which leads to high power consumption." He said, "The consequences of this are inefficient data rates and inflated storage. Frame-based video, which runs at 30 frames per second or 60 frames per second, can cause distortion in the captured image."

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