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  4. Bayesian multi-target tracking and sequential object recognition
 
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2008
Conference Paper
Title

Bayesian multi-target tracking and sequential object recognition

Abstract
Because of an increasing need and a rapid progress in the development of (unmanned) aerial vehicles and optical sensors that can be mounted onboard of these sensor platforms, there is also a considerable progress in 3D analysis of air- and UAV-borne video sequences. This work presents a robust method for multi-camera dense reconstruction as well as two important applications: creation of dense point clouds with precise 3D coordinates and, in the case of videos with Nadir perspective, a context-based method for urban terrain modeling. This method, which represents the main contribution of this work, includes automatic generation of digital terrain models (DTM), extraction of building outlines, modeling and texturing roof surfaces. A simple interactive method for vegetation segmentation is described as well.
Author(s)
Armbruster, W.
Mainwork
Automatic target recognition XVIII  
Conference
Conference "Automatic Target Recognition" 2008  
Open Access
File(s)
Download (244.99 KB)
Rights
Use according to copyright law
DOI
10.1117/12.776660
10.24406/publica-r-360268
Additional link
Full text
Language
English
FOM  
Keyword(s)
  • depth map

  • point cloud

  • urban terrain modeling

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