About the Project
EVOCATION is a leading European-wide doctoral Collegium for research in Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication. The Collegium will train the next generation of creative, entrepreneurial and innovative experts who will be equipped with the necessary skills and competences to face current and future major challenges in scalable and high-fidelity shape and appearance acquisition, extraction of structure and semantic information, processing, visualization, 3D display and 3D fabrication in professional and consumer applications.
The fellows will be early-stage scientific and industrial researchers (ESRs) who in the future will lead research and development of novel visual and geometric computing methodologies in the widest variety of applications, including industrial design and manufacturing, cultural heritage study and valorisation, geomatics, and tele-collaboration.
The EVOCATION network of public and private entities is naturally multidisciplinary and multi-institutional and will: (a) advance the state-of-the-art in geometry and material acquisition, geometry processing and semantic feature extraction, interactive visualization, computational fabrication, as well as high-bandwidth / 3D display systems; (b) bridge complementary approaches for cost-effective data digitization, visualization, fabrication, and display through the integration of different methodologies in the 3D capture, processing and fabrication pipeline; (c) promote, through domain-specific challenges, multidisciplinary research applied to concrete problems of the real world, in strict cooperation with end users in engineering, science and humanities; (d) demonstrate the feasibility and efficiency of scalable cost-effective end-to-end techniques to virtually and physically capture and create objects with complex shape and appearance; (e) increase awareness of the benefits of advanced visual and geometric computing technology in both professional and consumer domains.
This project has received funding from the European Union’s (EU) Horizon 2020 research and innovation program under Marie Skłodowska-Curie ITN Project under grant agreement No 813170.