ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2111.10196
11
20

Towards Traffic Scene Description: The Semantic Scene Graph

19 November 2021
Maximilian Zipfl
J. Marius Zöllner
    3DV
ArXivPDFHTML
Abstract

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.

View on arXiv
Comments on this paper