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HI! MY NAME IS

Roberto

Dr Roberto Mecca

Principal Research Scientist - Data

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My Story

I earned my PhD in Applied Mathematics in 2011, specializing in Computer Vision. Since then, I have pursued research in this field at esteemed institutions like the Technion - Israel Institute of Technology, Italian Institute of Technology, and Cambridge University. My primary research focus was on extracting precise 3D geometry from images, utilizing active light systems such as Photometric Stereo and traditional triangulation methods based on multi-view geometry. Subsequently, my research direction shifted towards application-driven projects. I worked at Toshiba Europe's Cambridge Research Laboratory and the High-Performance Vision Systems at the Austrian Institute of Technology, developing vision-based systems for quality control inspection technologies. Currently, at FullMatrix, I contribute to the development of non-contact inspection systems. My role involves analysing data from sophisticated ultrasound signal generation and propagation techniques.

Out of office

I have a passion for various camera-related activities, with photography and FPV drone piloting being my primary interests. In the realm of performing arts, I am drawn to music, appreciating both classical and pop genres, and I also have a keen interest in movies. Additionally, I am enthusiastic about keeping up with the latest developments in science and technology. I enjoy delving deep into these topics to gain a comprehensive understanding of their underlying principles.

Selected publications

Title
Authors
Publication/Event
Year
Real-time 6-DOF Pose Estimation by an Event Based Camera using Active LED Markers
G. Ebmer, A. Loch, M. N. Vu, R. Mecca, G. Haessing, C. Hartl-Nesic, M. Vincze, A. Kugi
Winter Conference on Applications of Computer Vision
2024
Photometric visibility matrix for the automatic selection of optimal viewpoints
V. Staderini, R. Mecca, T. Gluck, P. Schneider, A. Kugi
International Conference on 3D Vision
2024
Surface Sampling for Optimal Viewpoints Generation
V. Staderini, T. Gluck, P. Schneider, R. Mecca, A. Kugi
International Conference of Pattern Recognition Systems
2023
Spatial Resolution Metric for optimal viewpoints
V. Staderini, T. Gluck, P. Schneider, R. Mecca, A. Kugi
International Conference of Vision System
2023
A CNN Based Approach for the Point-Light Photometric Stereo Problem
F. Logothetis, R. Mecca, I. Budvytis, , R. Cipolla
International Journal of Computer Vision
2023
Modeling Partially Observable Systems using Graph-Based Memory and Topological Priors
S. Morad, S. Liwicki, R. Kortvelesy, R. Mecca and A. Prorok
Learning for Dynamics and Control
2022
LUCES: A Dataset for Near-Field Point Light Source Photometric Stereo
R. Mecca, F. Logothetis, I. Budvytis, R. Cipolla
British Machine Vision Conference
2021
PX-NET: Simple, Efficient Pixel-Wise Training of Photometric Stereo Networks
F. Logothetis, I. Budvytis, R. Mecca, R. Cipolla
International Conference on Computer Vision
2021
Embodied Visual Navigation with Automatic Curriculum Learning in Real Environments
S.D. Morad, R. Mecca, R.P.K. Poudel, S. Liwicki, R. Cipolla
IEEE Robotics and Automation
2021
A CNN Based Approach for the Near-Field Photometric Stereo Problem
F. Logothetis, I. Budvytis, R. Mecca, R. Cipolla
British Machine Vision Conference
2020
A Differential Volumetric Approach to Multi-View Photometric Stereo
F. Logothetis, R. Mecca, R. Cipolla
International Conference on Computer Vision
2019
A Differential Approach to Shape from Polarisation: a Level-Set Characterisation
F. Logothetis, R. Mecca, F. Sgallari and R. Cipolla
International Journal of Computer Vision
2019
A Differential Approach to Shape from Polarisation
R. Mecca, F. Logothetis and R. Cipolla
British Machine Vision Conference
2017
Photometric Stereo with Only Two Images: A Theoretical Study and Numerical Resolution
Y. Quèau, R. Mecca, J.D. Durou, X. Descombes
Image and Vision Computing
2017
Semi-calibrated Near Field Photometric Stereo
F. Logothetis, R. Mecca and R. Cipolla
Conference on Computer Vision and Pattern Recognition
2017
Unbiased Photometric Stereo for Colored Surfaces: A Variational Approach
Y. Quèau, R. Mecca and J.D. Durou
Conference on Computer Vision and Pattern Recognition
2016
Near-Field Photometric Stereo in Ambient Light
F. Logothetis, R. Mecca, Y. Quèau and R. Cipolla
British Machine Vision Conference
2016
A Single Lobe Photometric Stereo Approach for Heterogeneous Material
R. Mecca, Y. Quèau, F. Logothetis and R. Cipolla
SIAM Journal on Imaging Sciences
2016
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