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

Yuan, Jiangye; Cheriyadat, Anil M.

doi:10.1007/s00138-015-0722-x

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

Journal Article · Mon Oct 19 00:00:00 EDT 2015 · Machine Vision and Applications

DOI:https://doi.org/10.1007/s00138-015-0722-x· OSTI ID:1266007

Yuan, Jiangye ^[1]; Cheriyadat, Anil M. ^[1]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

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. Lastly, 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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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1266007

Journal Information:: Machine Vision and Applications, Vol. 27, Issue 1; ISSN 0932-8092

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 14 works

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A Method for Extracting Road Boundary Information from Crowdsourcing Vehicle GPS Trajectories Yang, Wei; Ai, Tinghua; Lu, Wei Sensors, Vol. 18, Issue 4 https://doi.org/10.3390/s18041261	journal	April 2018

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