5 papers
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…
Highly Automated Learning for Improved Active Safety of Vulnerable Road Users
Maarten Bieshaar, Günther Reitberger, Viktor Kreß +4
Highly automated driving requires precise models of traffic participants. Many state of the art models are currently based on machine learning techniques. Among others, the require…
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…