master Assignment
Heritage Biometrics – 3D acquisition design for fingerprints, scratches and toolmarks on works of art
Type: Master EE/CREATE (Creative Technology)
Student: Unassigned
Duration: TBD (min. 6 months/fulltime)
If you are interested please contact:
Background:
In decorative arts, human impressions, scratches, and toolmarks, are often visible on the surface of sculptures made of terracotta, wax, and even bronze. Acquiring fingerprints and other types of patterns on centuries-old art pieces and using different setups is still an underexplored area of investigation.
Goals:
In a joint effort between the DMB Lab and the fotostudio at CCNL (CollectieCentrum Nederland, Amersfoort), the student will design and implement different 3D acquisition setups of marks left on plasticine under different conditions (e.g., wet, dry, complete, partial). She/he will then also implement a visual interface such that the patterns of interest can be detected and easily browsed throughout the 3D model.
DMB Lab:
The Data Management & Biometrics Lab has the following depth camera’s available:
- Intel real sense (older models) (structured light);
- xbox 360 kinect v1 (structured light) https://all3dp.com/2/kinect-3d-scanner-easy-beginner-tutorial/
- Arducam (tof) https://www.arducam.com/time-of-flight-camera-raspberry-pi/
- Artec Eva (structured Light) https://www.artec3d.com/portable-3d-scanners/artec-eva
Supervisor and main contact: Dzemila Sero (assistant professor DMB)
Co-supervisor:
- Luuk Spreeuwers (associate professor DMB)
- Frans Pegt (senior photographer Rijksmuseum)
- Bieke van der Mark (art historian and curator, Rijksmuseum)
Your profile:
You are a graduate student with a strong experience in Sensor Design and Computer Vision. Part of the project requires critical thinking and exploring new directions, so you will also have the opportunity to go beyond current approaches.
Why join?
- Be part of a high-impact project that has the potential to substantially contribute to heritage science.
- Work at the intersection of hardware design and computer vision.
- Collaborate with a team of interdisciplinary experts of engineers, professionals in decorative arts and computer scientists.
Who Should Apply?
- Students with a strong background in hardware design and computer vision. Affinity or interest in the world of decorative arts is expected.
- Enthusiasts of computer vision for decorative arts, seeking to make a tangible impact in heritage science.
References:
- Sero, Dzemila, et al. "The study of three-dimensional fingerprint recognition in cultural heritage: Trends and challenges." Journal on Computing and Cultural Heritage (JOCCH) 14.4 (2021): 1-20.
- Sero, Dzemila, et al. "Artist profiling using micro-CT scanning of a Rijksmuseum terracotta sculpture." Science Advances 9.38 (2023): eadg6073.