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Bayesian multi-target tracking and sequential object recognition

: Armbruster, W.

Fulltext urn:nbn:de:0011-n-972493 (245 KByte PDF)
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Copyright 2008 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Created on: 19.9.2009

Sadjadi, F.A. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Automatic target recognition XVIII : 19 -20 March 2008, Orlando, Florida, USA
Bellingham, WA: SPIE, 2008 (Proceedings of SPIE 6967)
ISBN: 978-0-8194-7158-1
Paper 69670S
Conference "Automatic Target Recognition" <18, 2008, Orlando/Fla.>
Conference Paper, Electronic Publication
Fraunhofer FOM ( IOSB)
depth map; point cloud; urban terrain modeling

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.