January 22, 2015 -
Face and body Analysis Natural Computer Interaction (FANCI), a joint project focused on developing multimodal human-machine technologies, has received funding from Horizon 2020, the €80 billion European Union research and innovation program.
Led by project coordinator CEVA, the FANCI project centers on integrating multiple human-machine technologies on a single platform for greater power and cost efficiencies for application in a range of markets, with an initial focus on the automotive industry.
Collectively, the group will research, innovate, architect, design, develop and validate advanced multimodal face and body analytics and natural computer interfaces, establish a reference platform designed for a range of applications, and validate these innovations through user experience evaluation and benchmarking.
Each organization was chosen for their individual expertise. CEVA is a provider of CEVA-MM3101 imaging and vision platform and computer vision libraries for the human-machine technologies, HARMAN is an automotive industry expert, KeyLemon is a developer of face authentication software, nViso is a provider of emotion detection software, SoftKinetic is a developer of 3D vision technologies and gesture software, Tobii Technology is a provider of eye tracking technology, and the University of Siena is a developer of the application layer and the user API.
By integrating all of these capabilities in a reference architecture, the FANCI project will develop a creative automotive application-suite demonstrator, including an API for software application developers.
“This funding from the European Union will enable us to accelerate our collaborative efforts to develop a fully-featured multi-modal platform for a highly-immersive human-machine interactive experience,” said Shay Adar, director of technology collaborative programs at CEVA and coordinator of FANCI. “Integrating all of these technologies into single reference architecture for embedded products will serve to validate the cost and power savings achievable and enable us to demonstrate the true capabilities of a fully-featured human-machine user experience.”