The traveling optical scanner – case study on 3D shape models of ancient Brazilian skulls

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Recovering detailed morphological information from archaeological or paleontological material requires extensive hands-on time. Creating 3D scans based on e.g. computed tomography (CT) will recover the geometry of the specimen, but can inflict bimolecular degradation. Instead, we propose a fast, inoffensive and inexpensive 3D scanning modality based on structured light, suitable for capturing the morphology and the appearance of specimens. Benefits of having 3D models are manifold. The 3D models are easy to share among researchers and can be made available to the general public. Advanced morphological modelling is possible with accurate description of the specimens provided by the models. Furthermore, performing studies on models reduces the risk of damage to the original specimen. In our work we employ a high resolution structured light scanner for digitalizing a collection of 8500 year old human skulls from Brazil. To evaluate the precision of our setup we compare the structured light scan to micro-CT and achieve submillimetre difference. We analyse morphological features of the Brazilian skulls using manual landmarks, but a research goal is to automate this, fully utilize the dense 3D scans, and apply the method to many more samples.

TitelImage and Signal Processing : 7th International Conference, ICISP 2016, Trois-Rivières, QC, Canada, May 30 - June 1, 2016, Proceedings
RedaktørerAlamin Mansouri, Fathallah Nouboud, Alain Chalifour, Driss Mammass, Jean Meunier, Abderrahim Elmoataz
Antal sider8
ISBN (Trykt)978-3-319-33617-6
ISBN (Elektronisk)978-3-319-33618-3
StatusUdgivet - 2016
Begivenhed7th International Conference on Image and Signal Processing - Trois-Rivières, Canada
Varighed: 30 maj 20161 jun. 2016
Konferencens nummer: 7


Konference7th International Conference on Image and Signal Processing
NavnLecture notes in computer science

ID: 174006435