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Image feature based GPS trace filtering for road network generation and road segmentation

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Abstract

We propose a new method to infer road networks from GPS trace data and accurately segment road regions in high-resolution aerial images. Unlike previous efforts that rely on GPS traces alone, we exploit image features to infer road networks from noisy trace data. The inferred road network is used to guide road segmentation. We show that the number of image segments spanned by the traces and the trace orientation validated with image features are important attributes for identifying GPS traces on road regions. Based on filtered traces , we construct road networks and integrate them with image features to segment road regions. Our experiments show that the proposed method produces more accurate road networks than the leading method that uses GPS traces alone, and also achieves high accuracy in segmenting road regions even with very noisy GPS data.

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Notes

  1. http://www.openstreetmap.org/.

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Acknowledgments

This manuscript has been authored by employees of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. Accordingly, the United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

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  1. Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA

    Jiangye Yuan & Anil M. Cheriyadat

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  1. Jiangye Yuan
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  2. Anil M. Cheriyadat
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Correspondence to Jiangye Yuan.

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Yuan, J., Cheriyadat, A.M. Image feature based GPS trace filtering for road network generation and road segmentation. Machine Vision and Applications 27, 1–12 (2016). https://doi.org/10.1007/s00138-015-0722-x

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