Automatic Finding of Main Roads in Aerial Images by Using Geometric-Stochastic Models and Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Unbiased Detector of Curvilinear Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction to data compression
Introduction to data compression
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Contour Line and Geographic Feature Extraction from USGS Color Topographical Paper Maps
IEEE Transactions on Pattern Analysis and Machine Intelligence
CGI '99 Proceedings of the International Conference on Computer Graphics
Robust analysis of feature spaces: color image segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
From road maps to 3D-scenes: a reconstruction system
SCCG '03 Proceedings of the 19th spring conference on Computer graphics
Robust approach for suburban road segmentation in high-resolution aerial images
International Journal of Remote Sensing
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Geo-specific road modeling is an important aspect of driving simulation studies. A challenge in this operation is that it requires intensive manual work to collect data, interpret data, and create 3D models. Each of these components is time consuming. In this research, we propose a framework for fast geo-specific road modeling based on high-resolution aerial photos. This framework has been experimented on a real driving simulator.