Department of
Environmental Sciences, Informatics and Statistics

Artificial Intelligence and Image Understanding

The laboratory focuses on artificial intelligence, with particular emphasis on Machine Learning and Deep Learning techniques on geometric and structural data, quantum techniques for learning and characterizing structures (Quantum Machine Learning), Computer Vision and Stereometry.
It also boasts various international collaborations, and scientific and industrial projects, and is characterized by a strong propensity for wide international collaboration and multi-disciplinary research. The research results are applied to such diverse fields as oceanography, civil engineering, neuroimaging, analysis and conservation of cultural heritage, and analysis and characterization of environmental risk.

Research group

Collaborators

  • Alessia Cacchi
  • Francesco Pelosin
  • Fatima Tehreem
  • Alessandro Bicciato (Dottorando)
  • Shambel Fente Mengistu (Dottorando)

Collaborations

Publications

  • Pistellato, M., Bergamasco, F., Albarelli, A., Cosmo, L., Gasparetto, A., & Torsello, A. (2019). Robust phase unwrapping by probabilistic consensus. Optics and Lasers in Engineering, 121, 428-440
  • Bergamasco, F., Pistellato, M., Albarelli, A., & Torsello, A. (2020). Cylinders extraction in non-oriented point clouds as a clustering problem. Pattern Recognition, 107, 107443
  • Pistellato, M., Bergamasco, F., Torsello, A., Barbariol, F., Yoo, J., Jeong, J. Y., & Benetazzo, A. (2021). A physics-driven CNN model for real-time sea waves 3D reconstruction. Remote Sensing, 13(18), 3780
  • E. Rodolà, A. Albarelli, F. Bergamasco, A. Torsello, "A Scale Independent Selection Process for 3D Object Recognition in Cluttered Scenes." International Journal of Computer Vision, 102(1--3):129--145, https://doi.org/10.1007/s11263-012-0568-x, 2013
  • F. Bergamasco, A. Albarelli, L. Cosmo, E. Rodolà, A. Torsello, "An Accurate and Robust Artificial Marker based on Cyclic Codes." IEEE Transactions on Pattern Analysis and Machine Intelligence, https://doi.org/10.1109/TPAMI.2016.2519024, 38(12):2359--2373, 2016
  • E. Rodolà, L. Cosmo, M. Bronstein, A. Torsello, D. Cremers, "Partial Functional Correspondence." Computer Graphics Forum, https://doi.org/10.1111/cgf.12797, 36(1):222--236, 2017
  • A. Benetazzo, F. Ardhuin, F. Bergamasco, L. Cavaleri, P. V. Guimaraes, M. Schwendeman, M. Sclavo, J. Thomson, A. Torsello, "On the shape and likelihood of oceanic rogue waves." Scientific Reports, https://doi.org/10.1038/s41598-017-07704-9, 7(1):8276, 2017
  • M. Pistellato, F. Bergamasco, T. Fatima, and A. Torsello. "Deep Demosaicing for Polarimetric Filter Array Cameras." IEEE Transactions on Image Processing,  https://doi.org/10.1109/TIP.2022.3150296, 31: 2017-2026, 2022
  • L. Cosmo, G. Minello, M. Bronstein, E. Rodolà, L. Rossi, and A. Torsello. "3D Shape Analysis through a Quantum Lens: The Average Mixing Kernel Signature." International Journal of Computer Vision, https://doi.org/10.1007/s11263-022-01610-y, 130 (6): 1474-1493, 2022

Awards

Best paper of 2017 for the cathegory geoinformatics in the  journal Computes and Geosciences, for the paper:
Bergamasco et al., "WASS: An open-source pipeline for 3D stereo reconstruction of ocean waves."

Case studies

The Laboratory has been collaborating for years with the CNR ISMAR research institute in the field of 3D reconstruction of sea waves from off-shore platforms and ships. Cutting-edge techniques have been developed to efficiently and robustly estimate the space-time wave spectrum, which is essential for studying complex phenomena such as extreme wave statistics.

Equipment

  • Drone
  • Polarimetric cameras
  • Depth cameras

Research projects

  • PRIN2022 Project: EYE-FI.AI : going bEYond computEr vision paradigm using wi-FI signals in AI systems (Identification code: PRIN22 2022AL45R2), budget: € 74.345,00
  • PON Smart Cities Nazionali D.D. 391/Ric/05-07-2012 ADAPT - Accessible Data for Accessible Proto-Types in Social Sector
  • Research agreement with Istituto per le Scienze Marine (ISMAR) of the Consiglio Nazionale delle Ricerche (CNR) on the topic: Study on the 3D reconstruction of the ocean surface with an aim to study and measure whitecapping events
  • H2020-MSCA-IF-2014 - Marie Skodowska-Curie Individual Fellowships (IF-EF-RI) - European Fellowship, Reintegration Grant "VEiL - Visualising Engineered Landscapes: an archaeological approach to unlock environmental resilience and sustainability in antiquity."
  • Research agreement with Istituto per le Scienze Marine (ISMAR) of the Consiglio Nazionale delle Ricerche (CNR) on the topic: Study on the 3D reconstruction of the ocean surface with an aim to study and measure whitecapping events (reneweal)
  • Progetto di Ateneo 2016, University Ca’ Foscari Venezia: "Visual narrative of Venice through the centuries"
  • TEMART, tecnologie e materiali per la manifattura artistica, i Beni Culturali, l’arredo, il decoro architettonico e urbano e il design del futuro. POR FESR 2017
  • Time Machine, H2020-FETFLAG-2018-01H2020-FETFLAG-2018-01, EU Coordination & Support Action
  • "Tecniche di Deep Machine Learning per la classificazione automatica della qualità della frutta." FSE Project 2016, Interregional Projects, Smart Agrifood area
  • Industrial project "Consulenza per la definizione dei migliori processi allo stato dell'arte per la valutazione dei sistemi di calibrazione in uso dal committente" with CEMB s.p.a.
  • Industrial projects "WAVESENSE", "WAVESENSE2", "WAVESENSE3" with the Korean Institute of Ocean Science and Technology on the topic: Remote sensing systems pf the analysis of the ocean waves
  • Industrial projects "Compact Neural Networks for Camera Tasks" (CoNNeCT) ẅith SMACT competence centre
  • Research agreement with Istituto per le Scienze Marine (ISMAR) of the Consiglio Nazionale delle Ricerche (CNR) on the topic: "WAVENET: Deep Learning Techniques for Scattered Sea Surface Interpolation"

Last update: 23/04/2024