Unlike typical optical cameras, which can be blinded by bright light and unable to make out details in the dark, the NTU scientists say their smart camera can record the slightest movements and objects in real time.
The camera is said to record the changes in light intensity between scenes at nanosecond intervals, much faster than conventional video, and it stores the images in a data format that is many times smaller as well.
With a unique in-built circuit, the camera can do an instant analysis of the captured scenes, highlighting important objects and details.
“Our new camera can be a great safety tool for autonomous vehicles, since it can see very far ahead like optical cameras but without the time lag needed to analyse and process the video feed,” explained Chen Shoushun, Assistant Professor in NTU's School of Electrical and Electronic Engineering. “With its continuous tracking feature and instant analysis of a scene, it complements existing optical and laser cameras and can help self-driving vehicles and drones avoid unexpected collisions that usually happens within seconds.”
A typical camera sensor has several million pixels, which are sensor sites that record light information and are used to form a resulting picture.
High-speed video cameras that record up to 120 frames per second generate gigabytes of video data, which are then processed by a computer in order for self-driving vehicles to ‘see’ and analyse their environment.
The more complex the environment, the slower the processing of the video data, leading to lag times between ‘seeing’ the environment and the corresponding actions that the self-driving vehicle has to take.
To enable an instant processing of visual data, Celex records the changes between light intensity of individual pixels at its sensor, which reduces the data output. This avoids the need to capture the whole scene like a photograph, thus increasing the camera's processing speed.
The camera sensor also has a built-in processor that can analyse the flow of data instantly to differentiate between the foreground objects and the background, also known as optical flow computation. This innovation allows self-driving vehicles more time to react to any oncoming vehicles or obstacles.
Prof Chen and his researchers have spun off a start-up company named Hillhouse Tech to commercialise the camera technology, which is expected to be commercially ready by the end of this year.
