For the classification of traffic scenes, a description model is necessary that can describe the scene in a uniform way, independent of its domain. A model to describe a traffic scene in a semantic way is described in this paper. The description model allows to describe a traffic scene independently of the road geometry and road topology. Here, the traffic participants are projected onto the road network and represented as nodes in a graph. Depending on the relative location between two traffic participants with respect to the road topology, semantically classified edges are created between the corresponding nodes. For concretization, the edge attributes are extended by relative distances and velocities between both traffic participants wit...
The safety approval of Highly Automated Vehicles (HAV) is economically infeasible with current appro...
Abstract — Road recognition from video sequences has been solved robustly only for small, often simp...
Computer vision plays a central role in autonomous vehicle technology, because cameras are comparabl...
Understanding traffic scenes requires considering heterogeneous information about dynamic agents and...
Autonomous vehicles require an accurate understanding of the scene for safe operation in real-world ...
Semantic scene understanding plays a prominent role in the environment perception of autonomous vehi...
<p>Recent advances in representation learning have led to an increasing variety of vision-based appr...
In this paper, we are interested in understanding the semantics of outdoor scenes in the context of ...
Autonomous vehicles require an accurate and adequate representation of their environment for decisio...
Abstract — In this paper we propose a novel part-based approach to scene understanding, that allows ...
This paper tackles the challenge of scene understanding in context of automated driving. To react pr...
Examining graphs for similarity is a well-known challenge, but one that is mandatory for grouping gr...
The classification of semantically meaningful road markings in images is an important and safety cri...
Transportation, which deals with moving people and goods around, has a clear impact on the economic ...
We propose a method to recognize the traffic scene in front of a moving vehicle with respect to the ...
The safety approval of Highly Automated Vehicles (HAV) is economically infeasible with current appro...
Abstract — Road recognition from video sequences has been solved robustly only for small, often simp...
Computer vision plays a central role in autonomous vehicle technology, because cameras are comparabl...
Understanding traffic scenes requires considering heterogeneous information about dynamic agents and...
Autonomous vehicles require an accurate understanding of the scene for safe operation in real-world ...
Semantic scene understanding plays a prominent role in the environment perception of autonomous vehi...
<p>Recent advances in representation learning have led to an increasing variety of vision-based appr...
In this paper, we are interested in understanding the semantics of outdoor scenes in the context of ...
Autonomous vehicles require an accurate and adequate representation of their environment for decisio...
Abstract — In this paper we propose a novel part-based approach to scene understanding, that allows ...
This paper tackles the challenge of scene understanding in context of automated driving. To react pr...
Examining graphs for similarity is a well-known challenge, but one that is mandatory for grouping gr...
The classification of semantically meaningful road markings in images is an important and safety cri...
Transportation, which deals with moving people and goods around, has a clear impact on the economic ...
We propose a method to recognize the traffic scene in front of a moving vehicle with respect to the ...
The safety approval of Highly Automated Vehicles (HAV) is economically infeasible with current appro...
Abstract — Road recognition from video sequences has been solved robustly only for small, often simp...
Computer vision plays a central role in autonomous vehicle technology, because cameras are comparabl...