Towards Traffic Scene Description: The Semantic Scene Graph
This addresses the need for a standardized description model for traffic scene classification, but it is incremental as it builds on existing graph-based methods for scene representation.
The paper tackles the problem of uniformly describing traffic scenes for classification by introducing a semantic scene graph model that projects traffic participants onto a road network as nodes with semantically classified edges based on relative location, extended by attributes like distances and velocities. The result is a description model independent of road geometry and topology, easily convertible to machine-readable format.
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 with regard to the course of the lane. An important aspect of the description is that it can be converted easily into a machine-readable format. The current description focuses on dynamic objects of a traffic scene and considers traffic participants, such as pedestrians or vehicles.