Revatron has developed the world’s first smart camera enabling automobiles to learn distances and motions of objects just by using the camera. Revatron’s smart camera can also distinguish objects in motion from stationary ones by compensating for the movement of the vehicle. This camera embeds a real-time AI engine with a sub-one millisecond processing time. The real-time feature processing and ultra-low latency learning are optimized for automobile applications.

This breakthrough camera is based on Revatron’s DOORs (Direct Object-Oriented Reality system) technology, a real-time AI solution focusing on machine learning and 3D reality modeling. The camera can support from one to three camera inputs for 3D measurements. The DOORs camera’s passive design learns 3D depth information from the triangulation of multiple synchronized camera inputs. When using only a single camera input, the camera uses its own travelling path as the basis for triangulation.
The automobile industry has been looking for a LIDAR replacement due to its limitations in affordable mass production applications. Basically, LIDAR is a spinning radar system that requires a vantage point to survey its surroundings without blind spots. However, LIDAR is large, heavy, expensive, and not suited for high volume production. A typical autonomous driving system using LIDAR may require a 2KW computer to build a limited 3D model around the car in about 1.5 seconds.

Unlike LIDAR, the DOORs camera is a completely passive device that can be as small as a single compact drive recorder and mounted anywhere in a vehicle as an accessory to provide voice warnings or information on the surrounding area. The DOORs camera learns the 3D structures of the surroundings from only the camera inputs that don’t emit any lights or signals. The DOORs camera can provide the precise movements of surrounding objects if both GPS and speed data are available.