Visual models of plants interacting with their environment
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Modeling and animation of botanical trees for interactive virtual environments
Proceedings of the ACM symposium on Virtual reality software and technology
Interactive Modeling of Plants
IEEE Computer Graphics and Applications
Reconstructing 3D Tree Models from Instrumented Photographs
IEEE Computer Graphics and Applications
Finding Pictures of Objects in Large Collections of Images
ECCV '96 Proceedings of the International Workshop on Object Representation in Computer Vision II
CAIVL '97 Proceedings of the 1997 Workshop on Content-Based Access of Image and Video Libraries (CBAIVL '97)
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Visual Modeling with a Hand-Held Camera
International Journal of Computer Vision
An Efficient Solution to the Five-Point Relative Pose Problem
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D tree reconstruction from laser range data
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
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In this paper we propose a generative statistical approach for the three dimensional (3D) extraction of the branching structure of unfoliaged deciduous trees from urban image sequences. The trees are generatively modeled in 3D by means of L-systems. A statistical approach, namely Markov Chain Monte Carlo - MCMC is employed together with cross correlation for extraction. Thereby we overcome the complexity and uncertainty of extracting and matching branches in several images due to weak contrast, background clutter, and particularly the varying order of branches when projected into different images. First results show the potential of the approach.