Muhammad Arsalan Khawaja
About
About
Arsalan is a joint Ph.D. candidate at NTNU and Université de Bourgogne. He is focusing on developing new methods for the acquisition and appearance of surfaces with a Reflectance Transformation Imaging (RTI) setup.
Research Interests
- Reflectance Transformation Imaging
- Applied Machine Learning
- Control Systems
- Computer Vision
- Cultural Heritage Imaging
- Multispectral Imaging
Background and Experience
His previous research experiences include a Master's Thesis in EnCoV laboratory in Clermont-Ferrand, France on "Development of Computer Assisted Open Liver Surgery." He has a MSc (2021) in Vision and Robotics (VIBOT) from Université Bourgogne-Franche-Comté in France and Bachelor in Aerospace Engineering with majors in Control Systems from Institute of Space Technology, Pakistan.
He has also contributed to academia as a reviewer for Archiving Conference 2024.
Research
Arsalan is currently working in Colorlab at NTNU Gjøvik. His affiliations are as follows:
Publications
2023
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Khawaja, Muhammad Arsalan;
George, Sony;
Marzani, Franck;
Hardeberg, Jon Yngve;
Mansouri, Alamin.
(2023)
Can Surface Topography Give Us Best Light Positions for Reflectance Transformation Imaging?.
Archiving Conference
Academic article
-
Khawaja, Muhammad Arsalan;
George, Sony;
Marzani, Franck;
Hardeberg, Jon Yngve;
Mansouri, Alamin.
(2023)
An interactive method for adaptive acquisition in Reflectance Transformation Imaging for cultural heritage.
IEEE International Conference on Computer Vision Workshop (ICCVW)
Academic article
Journal publications
-
Khawaja, Muhammad Arsalan;
George, Sony;
Marzani, Franck;
Hardeberg, Jon Yngve;
Mansouri, Alamin.
(2023)
Can Surface Topography Give Us Best Light Positions for Reflectance Transformation Imaging?.
Archiving Conference
Academic article
-
Khawaja, Muhammad Arsalan;
George, Sony;
Marzani, Franck;
Hardeberg, Jon Yngve;
Mansouri, Alamin.
(2023)
An interactive method for adaptive acquisition in Reflectance Transformation Imaging for cultural heritage.
IEEE International Conference on Computer Vision Workshop (ICCVW)
Academic article