Fujitsu Limited and Carnegie Mellon University announced the development of a new technology to visualize traffic situations, including people and vehicles as part of joint research on Social Digital Twin that started in 2022. The technology transforms a 2D scene image captured by a monocular RGB camera into a digitalized 3D format using AI, which estimates the 3D shape and position of people and objects, enabling high-precision visualization of dynamic 3D scenes.
Starting February 22, 2024, Fujitsu and Carnegie Mellon University will conduct field trials utilizing data from intersections in Pittsburgh, USA, to verify the applicability of this technology. And this technology depends on AI that has been trained to detect the shape of people and objects through deep learning.
This system is based on 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 utilizing these technologies, images taken in situations in which people and cars are densely situated like intersections can be dynamically reconstructed in 3D virtual space, thus 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 anonymized to help preserve privacy.
Going forward, Fujitsu and Carnegie Mellon University aim to commercialize this technology by FY 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.
In February 2022, Fujitsu and Carnegie Mellon University’s School of Computer Science and College of Engineering began their joint research on Social Digital Twin technology, which dynamically replicates complex interplays between people, goods, economies, and societies in 3D.
These technologies enable the high-precision 3D reconstruction of objects from multiple photographs taken from videos shot from different angles. But as the joint research proceeded, it was found that existing video analysis methods were technically insufficient to dynamically reconstruct captured images to 3D. Multiple cameras were required to reproduce this, and there were issues with privacy, workload, and cost, which became a barrier to social implementation.
KEY QUOTES:
“This achievement is the result of collaborative research between Fujitsu’s team, Prof. Sean Qian, Prof. Srinivasa Narasimhan, and my team at CMU. I am delighted to announce it. CMU will continue to advance research on cutting-edge technologies through this collaboration in the future.”
- Prof. László A. Jeni, Assistant Research Professor, Carnegie Mellon University
“Our purpose is to make the world more sustainable by building trust in society through innovation. The Social Digital Twin technology we are developing aims to address a wide range of societal issues, aligning with this mission. I am thrilled to announce this milestone achieved in collaboration with CMU, marking a significant step towards our goal.”
- Daiki Masumoto, Fellow and Head of the Converging Technologies Laboratory of Fujitsu Research, Fujitsu Limited
