International Journal of Computer Vision

, Volume 23, Issue 3, pp 283–302 | Cite as

3D Pose Estimation by Directly Matching Polyhedral Models to Gray Value Gradients

  • Henner Kollnig
  • Hans-Hellmut Nagel


This contribution addresses the problem of pose estimation and tracking of vehicles in image sequences from traffic scenes recorded by a stationary camera. In a new algorithm, the vehicle pose is estimated by directly matching polyhedral vehicle models to image gradients without an edge segment extraction process. The new approach is significantly more robust than approaches that rely on feature extraction since the new approach exploits more information from the image data. We successfully tracked vehicles that were partially occluded by textured objects, e.g., foliage, where a previous approach based on edge segment extraction failed. Moreover, the new pose estimation approach is also used to determine the orientation and position of the road relative to the camera by matching an intersection model directly to image gradients. Results from various experiments with real world traffic scenes are presented.


Image Processing Real World Computer Vision Feature Extraction Image Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Kluwer Academic Publishers 1997

Authors and Affiliations

  • Henner Kollnig
    • 1
  • Hans-Hellmut Nagel
    • 1
    • 2
  1. 1.Institut für Algorithmen und Kognitive SystemeFakultät für Informatik der Universität Karlsruhe (TH)KarlsruheGermany
  2. 2.Fraunhofer-Institut für Informations- und Datenverarbeitung (IITB)KarlsruheGermany

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