Papers
8
Total Citations
71
H-Index
4
About
Dieter W. Fellner is a versatile computer scientist whose research spans computer graphics, collision detection, robotics, and the digital preservation of cultural heritage. His early foundational work on hierarchical spherical distance fields introduced a fast and broadly applicable collision detection technique for rigid bodies, earning 25 citations and demonstrating relevance across fields including CAD, robotics, and computational geometry. Over time, Fellner channeled his technical expertise into the critical challenge of 3D digitization, particularly within the GLAM sector — Galleries, Libraries, Archives, and Museums — contributing both to automated mass digitization workflows and robotic systems designed to capture cultural heritage artifacts with speed and fidelity. His 2022 outlook paper on 3D digitization reflects sustained engagement with European cultural heritage strategy and digital agenda priorities. Beyond heritage preservation, Fellner has explored practical robotics applications such as automated dismantling of nuclear power plants and virtual reality frameworks for distributed tele-experiments. More recently, his group has advanced image-based 3D reconstruction quality metrics and deep learning approaches for transparency detection. Across a career marked by interdisciplinary reach, Fellner exemplifies how foundational graphics research can evolve into real-world applications that serve both industry and society.
Research Focus
Key Achievements
Top Papers
- 1Hierarchical spherical distance fields for collision detection25 citations · 2006
- 2
- 3Towards 3D Digitization in the GLAM (Galleries, Libraries, Archives, and Museums) Sector. Lessons Learned and Future Outlook10 citations · 2022
- 4Virtual reality visualization of distributed tele-experiments9 citations · 2002
- 5
- 6
- 7Automated 3D Mass Digitization for the GLAM Sector2 citations · 2020
- 8