Country of Origin: United States of America
Host Institution: UBFC
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David obtained his Bachelor of Science in Imaging Science from the Chester F. Carlson Center for Imaging Science at the Rochester Institute of Technology in 2019. He briefly conducted undergraduate research in remote sensing before taking a position with a different professor to conduct multi- and hyperspectral image processing in cultural heritage as a part of the Rochester Cultural Heritage Imaging, Visualization, and Education (R-CHIVE) group.
Outside of RIT, David also spent a summer as part of the Higher Education Research Experiences (HERE) program at the Oak Ridge National Laboratory (ORNL) in the summer of 2018. At ORNL, he worked with the Geographic Information Science & Technology group to better understand the effects that image capture parameters could have in photogrammetry.
Aspirations within projects
David believes that his work as ESR9 is a logical extension of not only his imaging science background, but also the interest he has held in understanding imaging techniques better by taking a deeper dive into the image acquisition process. He also hopes to better connect with the European cultural heritage community.
ESR9: Appearance change assessment: Link between local geometry and global appearance descriptors
- Investigate the relation between changes in appearance and its underlying geometric mechanisms.
- Surface roughness reconstruction by combining stereo-photometry and ‘Shape From Focus’.
- Acquisition at the same scale of surface 3D information and the photometric attributes.
- Local and global singularities detection on 3D surfaces with impact on photometric attributes and global appearance.
- Model and reverse-model of the link between surface 3D and appearance through photometric attributes.
- Alamin Mansouri (UBFC)
- Robert Sitnik (WUT)
- Gaëtan LE GOIC (UBFC)
- Hermine Chatoux (UBFC)
- Nurit, M., G. Le Goic, D. Lewis, Y. Castro, A. Zendagui, H. Chatoux, H. Favreliere, S. Maniglier, P. Jochum, A. Mansouri (2021). HD-RTI: An adaptive multi-light imaging approach for the qualityassessment of manufactured surfaces. Computers in Industry, Vol. 132. ISSN 0166-3615.
- Lewis, D.A., M. Nurit, H. Chatoux, F. Meriaudeau, A. Mansouri (2021) : An automated adaptive focus pipeline for reflectance transformation imaging. Society for Imaging Science and Technology, IS&T International Symposium on Electronic Imaging 2021.