Multi-sensorial Urban Environment Perception


In the past decade we have witnessed an explosion of new technologies for acquisition and understanding of environmental information. 3D vision systems of self-driving vehicles can be used for -apart from safe navigation- real time mapping of the environment, detecting and analyzing static (traffic signs, power lines, vegetation, street furniture), and dynamic (traffic flow, crowd gathering, unusual events) scene elements. On the other hand, new generation geo-information systems (GIS) store extremely detailed 3D maps about the cities, consisting of dense 3D point clouds, registered camera images and semantic metadata.

In this talk, I present new techniques to facilitate the joint exploitation of the measurements of car mounted online sensing platforms, and offline 3D environmental data obtained by Mobile Laser Scanning (MLS) technology in urban environment.

  • First RangeMRF, a Lidar based real time and accurate self-localization and change detection approach is presented for self-driving vehicles, using as reference high resolution 3D point cloud maps of the environment obtained through Mobile Laser Scanning (MLS).
  • Second, we propose an end-to-end, fully automatic, online camera- Lidar calibration approach, for application in self-driving vehicle navigation.
  • Finally, ChangeGAN, a novel deep neural network-based change detection approach is introduced, which can robustly extract changes between sparse and weakly registered point clouds obtained in a complex street-level environment, tolerating up to 1m translation and 10 degrees rotation misalignment between the corresponding 3D point cloud frames.

About the speaker:

Prof Dr Csaba Benedek (PhD, DSc, dr. habil) is a scientific advisor with the Machine Perception Research Laboratory of the Institute for Computer Science and Control (SZTAKI) in Budapest, Hungary where he is the head of the Research Group on Geo-Information Computing. He also works as a full professor with the Faculty of Information Technology and Bionics of the Péter Pázmány Catholic University, teaching Basic Image Processing Algorithms in the first semester of IPCV.

Between 2008 and 2009 he was a postdoctoral researcher at INRIA Sophia-Antipolis, working in the Ariana Project Team.

Dr Benedek is the current president of the Hungarian Image Processing and Pattern Recognition Society (Képaf), the vice chairman of the John von Neumann Computer Society, and the Hungarian Governing Board Member of the International Association for Pattern Recognition (IAPR).

He is a Senior Member of IEEE, and an Associate Editor of Digital Signal Processing (Elsevier) journal.

He received various awards including the Bolyai plaquette from the Hungarian Academy of Sciences (HAS) 2019, Imreh Csanád supervisor plaquette from the Hungarian National Scientific Student Conference (OTDK) (2019), and the Michelberger Master Award from the Hungarian Academy of Engineering (2020). He has been the manager of various national and international research projects in the recent years.

His research interests include Bayesian image and point cloud segmentation, object extraction, change detection, machine learning applications and GIS data analysis.

We are using cookies to give you the best experience. You can find out more about which cookies we are using or switch them off in privacy settings.
AcceptPrivacy Settings