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Point Cloud Research Group

Dr. Tamas Lovas

Associate Professor

PhD

H-1111 Budapest Muegyetem rkp. 3.

+3614362223

lovas.tamas@emk.bme.hu

Dr. Somogyi József Árpád

Assistant Professor

Dr. Bence Attila Molnár

Associate Professor

Introduction of the Research Group

The Point Cloud Research Group is engaged in basic and applied research on the collection, storage, analysis and visualization of point clouds for engineering and scientific purposes. Point clouds can come from a variety of sources, eg laser scanners, cameras; the research group addresses data collection requirements, technological parameters, sensor integration options according to the needs of the application. The research team will also be responsible for the preparation, filtering and storage of the collected data; the development of efficient workflows to support this. In the field of processing and analysis, semi-automatic and automatic procedures are developed, eg segmentation, classification, modeling, object recognition. In the area of ​​data visualization, the research team will work on visualization technologies (eg VR/AR visualization), database connections, 3D printing at different modeling levels of point clouds. The research group has a strong focus on developing an efficient workflow to meet the needs of a given application domain. Where appropriate, it is necessary to combine several data collection processes (eg ground laser scanning and drone photogrammetry), to combine data (eg geometric data and color information), to combine data processing steps (eg segmentation-classification workflow). In addition to traditional visualization methods, we use technologies (eg AR applications) to support non-experts in interpreting data. Where appropriate, it is necessary to combine several data collection processes (eg ground laser scanning and drone photogrammetry), to combine data (eg geometric data and color information), to combine data processing steps (eg segmentation-classification workflow). In addition to traditional visualization methods, we use technologies (eg AR applications) to support non-experts in interpreting data. Where appropriate, it is necessary to combine several data collection processes (eg ground laser scanning and drone photogrammetry), to combine data (eg geometric data and color information), to combine data processing steps (eg segmentation-classification workflow). In addition to traditional visualization methods, we use technologies (eg AR applications) to support non-experts in interpreting data.

Watch our 3-minute introductory video:

Achievements

- Point cloud models to support automotive applications (eg vehicle dynamics simulations, autonomous vehicle development)
- Engineering geological analyzes (eg determination of fault planes) based on point clouds
- Structural monitoring applications based on point clouds (eg bridge inspection)
- Support for point cloud-based architectural heritage applications
- Point cloud modeling of objects (eg architectural stone fragments, engineering elements)

Publications

Lovas, Tamas ; Ormandi, Tamas ; Somogyi, Jozsef Arpad ; Baranyai, Daniel ; Tihanyi, Viktor ; Tettamanti, Tamas
OpenCRG models from different data sources to support vehicle simulations
IEEE ACCESS 10 pp. 42690-42698. , 9 p.m. (2022)
Lovas, Tamás ; Somogyi, József Árpád ; Simongáti, Győző
Laser Scanning Ship Hulls to Support Hydrodynamic Simulations
PERIODICA POLYTECHNICA-CIVIL ENGINEERING 66 : 1 pp. 291-297. , 7 p.m. (2021)
Török, Ákos ; Bögöly, Gyula ; Somogyi, Árpád ; Lovas, Tamás
Application of UAV in Topographic Modeling and Structural Geological Mapping of Quarries and Their Surroundings—Delineation of Fault-Bordered Raw Material Reserves
SENSORS 20 : 2 p. 489, 19 p. (2020)
Csiszár, Csaba ; Csonka, Bálint ; Földes, Dávid ; Wirth, Ervin ; Lovas, Tamás
Urban public charging station locating method for electric vehicles based on land use approach
JOURNAL OF TRANSPORT GEOGRAPHY 74 pp. 173-180. , 8 p.m. (2019)
Somogyi, Árpád ; Fehér, Kristina ; Lovas, Tamás ; Halmos, Balázs ; Barsi, Árpád
Analysis of Gothic Architectural Details by Spatial Object Reconstruction Techniques
PERIODICA POLYTECHNICA-CIVIL ENGINEERING 61 : 3 pp. 640-651. , 12 p. (2017)

Journals

IEEE Access, Journal of Transport Geography, Sensors, Remote Sensing, ISPRS Archives, ISPRS Annals, PE&RS, Journal of Photogrammetry

Infrastructure

terrestrial laser scanner, mobile laser scanner, unmanned aerial aircraft, camera

Projects

Innovative decision support using the automation, digitization and optimization of civil engineering work processes, 2020-2023, 2019-1.1.1-PIACI-KFI-2019-00238, NKFIH
TKP2020 BME-NKA, 2020-2022, NKFIH
within the Excellence Program for Higher Education Institutions in Budapest Technical and University of Economics Artificial Intelligence (BME FIKP-MI/FM) thematic program
Satellite Applications For Emergency handling, Traffic alerts, Road safety and Incident Prevention (SafeTrip), EU FP7, 2009-2012
Cooperative systems for road safety "Smart Vehicles on Smart Roads" (SafeSpot), EU FP6 Information Society technologies Integrated Project, 2006-2010
Traffic Eye, EU INTAS program, 2005-2006

Industry relations

4iG Mnesor3D, NNG

Conferences

ISPRS and ASPRS conferences