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Environment Sensing and Machine Vision Research Group

Dr. Tamás Szirányi

Professor

DSc

H-1111, Budapest, BME L building

+3614632236

sziranyi.tamas@kjk.bme.hu

Zoltan Rozsa

Research fellow

Marcell Golarits

PhD Student

Sándor Gazdag

PhD Student

Introduction of the Research Group

The Machine and Vehicle Vision Research Group deals with vision of automated machines that surround us (robots, mobile machines, vehicles). In the field of vehicle, transport and material handling systems, machine vision and intelligent sensor networks, as well as machine-human collaboration have become of decisive importance and their role is growing.
Our research topics:
- general machine vision
- human-machine interface (HMI) and biometric personal identification, motion analysis,
- co-operative working space, in human-machine collaboration
- intelligent sensor networks
- 3D camera networks and positioning devices.
Some of our previous work:
- collaborative UAV systems
- applying cameras and laser scanners on vehicles for environment perception and understanding
- navigation of automated guided vehicles using image processing systems
- camera systems in traffic control

Achievements

  • Development of novel Simultaneous Localization and Mapping algorithms
  • 3D geometry in environment reconstruction and recognition
  • Dep learning applications in automated vehicles

Publications

Csaba Benedek, Andras Majdik, Balazs Nagy, Zoltan Rozsa, Tamas Sziranyi, Positioning and perception in LIDAR point clouds, Digital Signal Processing, Volume 119, 2021, 103193, ISSN 1051-2004, https://doi.org/10.1016/j.dsp.2021.103193.

V. Hosu, H. Lin, T. Sziranyi and D. Saupe, "KonIQ-10k: An Ecologically Valid Database for Deep Learning of Blind Image Quality Assessment," in IEEE Transactions on Image Processing, vol. 29, pp. 4041-4056, 2020, doi: 10.1109/TIP.2020.2967829.

D. Rozenberszki and A. L. Majdik, "LOL: Lidar-only Odometry and Localization in 3D point cloud maps," 2020 IEEE International Conference on Robotics and Automation (ICRA), 2020, pp. 4379-4385, doi: 10.1109/ICRA40945.2020.9197450.

Z. Rozsa and T. Sziranyi, "Obstacle Prediction for Automated Guided Vehicles Based on Point Clouds Measured by a Tilted LIDAR Sensor," in IEEE Transactions on Intelligent Transportation Systems, vol. 19, no. 8, pp. 2708-2720, Aug. 2018, doi: 10.1109/TITS.2018.2790264.

Majdik AL, Till C, Scaramuzza D. The Zurich urban micro aerial vehicle dataset. The International Journal of Robotics Research. 2017;36(3):269-273. doi:10.1177/0278364917702237

Journals

IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Intelligent Vehicles
Digital Signal Processing
The International Journal of Robotics Research
Pattern Recognition Letters

Infrastructure

Environment perception sensors like camera systems and LIDARS

Projects

2018-1.3.1-VKE-2018-00021:: Development of intelligent transportation control system, 2019-2022
FIKP FM, 2018-2019

Industry relations

Gamax
Knorr-Bremse
Bosch

Conferences

International Symposium on Robotics (ISR Europe), 2022, Sandor Gazdag, presenter
International Conference on Image Analysis and Processing (ICIAP), 2022, Tamas Sziranyi, Zoltan Rozsa, presenter
IEEE International Conference on Robotics and Automation (ICRA), 2020, Andras Majdik, presenter
International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS), 2020, Zoltan Rozsa, presenter
International conference on multimedia and network information system,2019, Andras Majdik, presenter