From GPS traces to a routable road map
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
A prsimonious model of mobile partitioned networks with clustering
COMSNETS'09 Proceedings of the First international conference on COMmunication Systems And NETworks
Map inference in the face of noise and disparity
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
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The trace data generated from GPS enabled vehicles is highly valuable for applications such as map inference and traffic analysis. However, the data tends to be noisy due to signal interference. In this paper, we introduce aerial images in GPS trace analysis. Computer vision techniques are developed that effectively integrate image information with GPS data to generate road networks. An image is first segmented by an efficient factorization-based algorithm. A structure tensor approach is proposed to measure the orientation difference between a trace segment and the corresponding image patch. The segmentation result and orientation measures lead to significantly reducing the traces not aligning with roads. The traces are further processed to produce high-quality road networks. We show that our method produces promising results for very noisy GPS data with a low sampling rate and also outperforms the leading method of map inference from GPS traces.