Geometric Computer Vision
Description of Activities
The main research field of the group is 3D machine perception. Principally, we process camera images, depth sensors, and LiDAR devices. The main active research topics are
- Calibration of different modalities, especially LiDAR devices and digital cameras.
- Stereo vision exploiting affine transformations.
- Visual odometry using vehicle-mounted sensors.
The application of affine transformations is the main focus of our research. This topic originated at ELTE.
The main application field is autonomous driving. At the university, a sensor-kit has been developed including cameras with narrow and wide field-of-view lenses, LiDAR sensor(s), IMU and RTK-GPS. The sensors are synchronized in time. A remotely controllable electric go-kart has been constructed here.
A programmable robotic arm is also developed for which the goal is the automatic unpacking of boxes; our research group developed a 2D LiDAR-based measuring software to detect the dimensions of the object that is gripped by the robot.
The group yearly organizes a competition for students, autonomous driving related tasks should be solved by the participants.
Our research work is supported by Robert Bosch GmbH.
Research Interests
Stereo and Multi-view 3D Computer Vision
- 3D Reconstruction
- Structure from Motion /Simultaneous Localization and Mapping
- Visual odometry
Multi-modal calibration
- Camera LiDAR
- Multi LiDARs
- 2D LiDARs
- RGB-D sensors
Research/service concepts/Methodology
We believe that theory and practice meet in modern research. Therefore, we address problems that appear in real-life applications. We prefer to use our own testing data, we do not only download those from the Internet. For this reason, we have developed (i) ELTECar: a car equipped with several sensors and (ii) ELTEKart: a remotely controllable electric go-kart.
Research Staff
- Levente Hajder (head), senior researcher
- Lajos Loczi, senior researcher
- Iván Eichhardt, senior researcher
- Bandó Kovács, engineer
- Tekla Tóth, PhD student
- Tamás Tófalvi, PhD student
- Máté Cserép, PhD student
Projects
- 3D reconstruction from rectified stereo images using affine transformations
- Machine vision for an unpacking robot
- LiDAR-camera calibration using spherical calibration objects
- Calibration of multi 2D LiDAR sensors
- Homography estimation for offside detection using the center circle
5 important publications in the field
- Tóth, T. and Hajder, L. (2023) ’A Minimal Solution for Image-Based Sphere Estimation’, International Journal of Computer Vision, 131(6), pp. 1428–1447.
- Hajder, L. and Baráth, D. (2020) ’Relative planar motion for vehicle-mounted cameras from a single affine correspondence’, 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020, pp. 8651–8657.
- Baráth, D., Eichhardt, I. and Hajder, L. (2019) ’Optimal Multi-View Surface Normal Estimation Using Affine Correspondences’, IEEE Transactions on Image Processing, 28(7), pp. 3301–3311.
- Baráth, D. and Hajder, L. (2018) ’Efficient Recovery of Essential Matrix From Two Affine Correspondences’, IEEE Transactions on Image Processing, 27(11), pp. 5328–5337.
- Barath, D., Toth, T. and Hajder, L. (2017) ’A Minimal Solution for Two-View Focal-Length Estimation Using Two Affine Correspondences’, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA, 2017, pp. 2557–2565.
Infrastructure
ELTECar testing car and ELTEKart controllable go-kart
16-beam Velodyne VLP-16 LiDARs
HikVision 2 MPixel color cameras. With normal and fisheye optics
RTK compensation GPS
Intel Intellysense depth camera