About
I am currently working as a Project Assistant at the Institute of Visual Computing at Graz University of Technology, Austria.
Alongside my work, I am pursuing a PhD in Computer Science under the supervision of Prof. Dr. Horst Bischof (currently the rector of Graz University of Technology) and Dr. Horst Possegger.
I received my master’s degree in Mathematics from M.V.Lomonosov Moscow State University (MSU), graduating from the Faculty of Mechanics and Mathematics — a globally recognized university with a strong reputation in academic and research mathematical circles, known since the time of Kolmogorov, Chebyshev, and many other outstanding mathematicians who worked there.
My primary research interests lie in Deep Neural Networks (AI) for Intelligent Video Surveillance Systems, Autonomous Driving, and Automated Industrial Processing, with a particular focus on video scene understanding, multiple object detection and tracking, and domain adaptation.
Our team works closely with leading industry partners such as Infineon Technologies, AVL List, ASFINAG, KNAPP, Saubermacher, and others, to develop and transfer cutting-edge technologies into real-world industrial applications.
We also collaborate on government- and city-funded projects (e.g., by the Federal Ministry for Climate Protection, Environment, Energy, Mobility, Innovation and Technology (BMK)), integrating smart technologies into sustainable traffic management and urban planning to enhance road-user safety, especially for pedestrians and cyclists.
My Projects
Multimodal Domain Adaptation for Air Traffic Management
Fog Simulation for Testing Vision-Based AI Systems
Monocular Depth Estimation in Real-World Environments
Tracking Road Users for Improved Traffic Safety
Understanding Pedestrian Behavior at Crosswalks
Safety Crosswalks Planning Using Movement Patterns
Compliance with Traffic Light Signals for Pedestrian Safety
Pedestrian Awareness of Approaching Vehicle and Traffic Risks
Pedestrian Distractions in Traffic Environments
Traffic Safety for People with Limited Mobility
Enhancing Pedestrian Monitoring with ToF Sensors
Improving Detection of Pedestrians and Cyclists with LiDAR
Camera – LiDAR Calibration for Multisensor Perception Systems
Cross-View Calibration Between In-Vehicle and Roadside Cameras
Automated Robust Anonymization of Vehicle License Plates in Videos
My Publications
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Into the Fog: Evaluating Robustness of Multiple Object Tracking
In Proc. of the British Machine Vision Conference (BMVC), 2024
PaperProceedings Cite this paperSupplementaryPosterCodeBibTeX:
@inproceedings{Kirillova_2024_BMVC,
title = {{Into the Fog: Evaluating Robustness of Multiple Object Tracking}},
author = {Kirillova, Nadezda** and Mirza, M. Jehanzeb and Bischof, Horst and Possegger, Horst},
booktitle = {In Proc. of the British Machine Vision Conference (BMVC)},
year = {2024}
}
-
A Comprehensive Crossroad Camera Dataset to Improve Traffic Safety of Mobility Aid Users
In Proc. of the British Machine Vision Conference (BMVC), 2023
Paper Cite this paperSupplementaryPosterVideoCodeDatasetBibTeX:
@inproceedings{mohr23a,
title = {{A Comprehensive Crossroad Camera Dataset to Improve Traffic Safety of Mobility Aid Users}},
author = {Mohr, Ludwig and Kirillova, Nadezda and Possegger, Horst and Bischof, Horst},
booktitle = {In Proc. of the British Machine Vision Conference (BMVC)},
year = {2023}
}
-
Identifying and Extracting Pedestrian Behavior in Critical Traffic Situations
In Proc. of the IEEE International Conference on Intelligent Transportation Systems (ITSC), 2023
Paper Cite this paperBibTeX:
@inproceedings{schachner23b,
title = {{Identifying and Extracting Pedestrian Behavior in Critical Traffic Situations}},
author = {Schachner, Martin and Schneider, Bernd and Wei{\ss}enbacher, Fabian and Kirillova, Nadezda and Possegger, Horst and Bischof, Horst and Klug, Corina},
booktitle = {In Proc. of the IEEE International Conference on Intelligent Transportation Systems (ITSC)},
year = {2023}
}
-
Observation-based Pedestrian Scenario Extraction for Virtual Testing
In Proc. of the International Technical Conference on the Enhanced Safety of Vehicles (ESV), 2023
Proceedings Cite this paperBibTeX:
@inproceedings{schachner23a,
title = {{Observation-based Pedestrian Scenario Extraction for Virtual Testing}},
author = {Schachner, Martin and Kirillova, Nadezda and Wei{\ss}enbacher, Fabian and Schneider, Bernd and Possegger, Horst and Bischof, Horst and Aichberger, Arno and Magosi, Zoltan Ferenc and Dobberstein, Jan and Lich, Thomas and Kirchengast, Martin and Hennecke, Marcus and Klug, Corina},
booktitle = {In Proc. of the International Technical Conference on the Enhanced Safety of Vehicles (ESV)},
year = {2023}
}
-
A Visual Surveillance System to Observe Realistic Road User Behavior for Improved Pedestrian and Cyclist Safety at Crossroads
In Proc. of the IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS), 2022
Paper Cite this paperBibTeX:
@inproceedings{kirillova22a,
title = {{A Visual Surveillance System to Observe Realistic Road User Behavior for Improved Pedestrian and Cyclist Safety at Crossroads}},
author = {Kirillova, Nadezda and Possegger, Horst and Bischof, Horst},
booktitle = {In Proc. of the IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS)},
year = {2022}
}