6 papers · 1 filter
Cyclist Trajectory Forecasts by Incorporation of Multi-View Video Information
Stefan Zernetsch, Oliver Trupp, Viktor Kress +2
This article presents a novel approach to incorporate visual cues from video-data from a wide-angle stereo camera system mounted at an urban intersection into the forecast of cycli…
Pose and Semantic Map Based Probabilistic Forecast of Vulnerable Road Users' Trajectories
Viktor Kress, Fabian Jeske, Stefan Zernetsch +2
In this article, an approach for probabilistic trajectory forecasting of vulnerable road users (VRUs) is presented, which considers past movements and the surrounding scene. Past m…
Cyclist Intention Detection: A Probabilistic Approach
Stefan Zernetsch, Hannes Reichert, Viktor Kress +2
This article presents a holistic approach for probabilistic cyclist intention detection. A basic movement detection based on motion history images (MHI) and a residual convolutiona…
Intentions of Vulnerable Road Users - Detection and Forecasting by Means of Machine Learning
Michael Goldhammer, Sebastian Köhler, Stefan Zernetsch +3
Avoiding collisions with vulnerable road users (VRUs) using sensor-based early recognition of critical situations is one of the manifold opportunities provided by the current devel…
Early Start Intention Detection of Cyclists Using Motion History Images and a Deep Residual Network
Stefan Zernetsch, Viktor Kress, Bernhard Sick +1
In this article, we present a novel approach to detect starting motions of cyclists in real world traffic scenarios based on Motion History Images (MHIs). The method uses a deep Co…
Cooperative Starting Movement Detection of Cyclists Using Convolutional Neural Networks and a Boosted Stacking Ensemble
Maarten Bieshaar, Stefan Zernetsch, Andreas Hubert +2
In future, vehicles and other traffic participants will be interconnected and equipped with various types of sensors, allowing for cooperation on different levels, such as situatio…