TractorEYE: Vision-based Real-time Detection for Autonomous Vehicles in Agriculture

PhD defence, Friday 3 November 2017. Peter Christiansen.

2017.11.03 | Liselotte Kaspersen Heller

Peter Christiansen

TractorEYE is a multi-modal real-time detection system developed in the dissertation to give tractors the ability to “see”. A key contribution of the detection system is a camera-based anomaly detection algorithm that is able to detect heavy occluded, unknown and very distant obstacles in real-time.

During his studies, Peter Christiansen researched procedures to realize autonomous vehicles in agriculture. To get fully autonomous vehicles certified for farming, computer vision algorithms and sensor technologies must detect obstacles with equivalent or better than human-level performance. Peter Christiansen studied deep learning-based algorithms to improve the ability of tractors to “sense” the surroundings and to detect obstacles.

The contributions of this thesis have demonstrated, addressed and solved critical issues to utilize camera-based perception systems that are essential to make autonomous vehicles in agriculture a reality.

The PhD degree was completed at the Department of Engineering, Science and Technology, Aarhus University.

This résumé was prepared by the PhD student.

Time: Friday 3 November 2017 at 13:00
Place: Building 5125, room 403, Finlandsgade 22, 8200 Aarhus N.
Title of dissertation: TractorEYE: Vision-based Real-time Detection for Autonomous Vehicles in Agriculture
Contact information: Peter Christiansen, e-mail:, tel.: +45 27592953
Members of the assessment committee:
Professor Thomas B. Moeslund, Department of Department of Architecture, Design and Media Technology, Aalborg University
Associate Professor Anastasios Tefas, Department of Informatics, Aristotle University of Thessaloniki
Associate Professor Stefan Hallerstede, Department of Engineering, Aarhus University (chair)
Main supervisor:
Senior Researcher Rasmus Nyholm Jørgensen, Department of Engineering, Aarhus University
Professor (Docent) Henrik Karstoft, Department of Engineering, Aarhus University
Language: The PhD dissertation will be defended in English

The defence is public.
The dissertation is available for reading at the Graduate School of Science and Technology/GSST, Ny Munkegade 120, building 1520, rooms 128-134, 8000 Aarhus C.

PhD defence
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Revised 23.02.2018