Fujitsu and Carnegie Mellon University has announced the development of a new technology to visualise traffic situations, including people and vehicles, as part of joint research on Social Digital Twin that began in 2022. The technology transforms a 2D scene image captured by a monocular RGB camera into a digitalised 3D format using AI, which estimates the 3D shape and position of people and objects enabling high-precision visualisation of dynamic 3D scenes. Starting February 2024, Fujitsu and Carnegie Mellon University will conduct field trials leveraging data from intersections in Pittsburgh, USA, to verify the applicability of this technology.
This technology relies on AI that has been trained to detect the shape of people and objects through deep learning. This system is composed of two core technologies: 1) 3D Occupancy Estimation Technology that estimates the 3D occupancy of each object only from a monocular RGB camera, and 2) 3D Projection Technology that accurately locates each object within 3D scene models. By utilising these technologies, images taken in situations in which people and cars are densely situated, such as at intersections, can be dynamically reconstructed in 3D virtual space, thereby providing a crucial tool for advanced traffic analysis and potential accident prevention that could not be captured by surveillance cameras. Faces and license plates are anonymised to help preserve privacy.
Going forward, Fujitsu and Carnegie Mellon University aim to commercialise this technology by 2025 by verifying its usefulness not only in transportation but also in Smart Cities and traffic safety, with the aim of expanding its scope of application.
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