An ultrafast high-contrast camera developed in Singapore could help self-driving cars and drones "see" better in adverse road and weather conditions. The smart camera, created by a team of scientists from Nanyang Technological University (NTU), can record the slightest of movements and objects in real-time, even when blinded by bright light or in complete darkness. The new camera records changes in light intensity between scenes at nanosecond intervals, much faster than conventional video, and stores the images in a smaller data format as well. NTU Singapore assistant professor Shoushun Chen has developed an ultrafast camera with a unique built-in circuit, allowing instant analysis of captured scenes. Courtesy of NTU Singapore. Developed by assistant professor Shoushun Chen from NTU's School of Electrical and Electronic Engineering, the new camera, named Celex, is in its final prototype phase. "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 analyze and process the video feed," said Chen. "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 happen within seconds." A typical camera sensor has several millions 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 or photos per second generate gigabytes of video data, which are then processed by a computer in order for self-driving vehicles to "see" and analyze 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. NTU’s patent-pending camera enables instant processing of visual data. The Celex records the changes between light intensity of individual pixels at its sensor, reducing the data output and increasing processing speed. The camera sensor also has a built-in processor that can analyze 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. Chen expects the camera to be commercially available by the end of the year and is currently in talks with several global electronic manufacturers.