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  4. 3D pose estimation by directly matching polyhedral models to gray value gradients
 
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1997
Journal Article
Title

3D pose estimation by directly matching polyhedral models to gray value gradients

Abstract
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.
Author(s)
Kollnig, H.
Nagel, H.-H.
Journal
International Journal of Computer Vision  
DOI
10.1023/A:1007927317325
Language
English
IITB  
Keyword(s)
  • image sequence analysis

  • Kalman filter

  • motion analysis

  • object recognition

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