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D-SYNC: Enhancing Vehicle Localization with Dashcam-Satellite Image Synchronization

  • Peng Jiang
  • , Liuwan Zhu
  • , Rui Ning
  • , Hongyi Wu
  • , Chunsheng Xin

Research output: Contribution to journal › Conference article › peer-review

Abstract

This paper introduces D-SYNC, a cutting-edge framework for enhancing the security and reliability of vehicle localization systems. D-SYNC offers an innovative solution to utilize dashcam footage for vehicle localization in the scenario of the primary localization system, GPS, under security attacks or simply failing to work. D-SYNC synchronizes the visual data from dashcam recordings with geotagged satellite imagery, achieving reliable vehicle positioning and trajectory mapping without precise dashcam-to-satellite alignment. D-SYNC introduces novel designs to address critical challenges, such as the limited field of vision in dashcam videos during real-world driving and how to correlate the significantly distinct spatial and temporal patterns between dashcam sequences and satellite images. Moreover, a novel geo-assisted loss function is introduced in D-SYNC that further elevates the performance of the localization process. D-SYNC surpasses existing methods and significantly increases vehicle localization accuracy. It achieves a 91% top-1 retrieval accuracy in urban environments and a 34% improvement in sub-10 meter localization error compared to benchmarks, relying solely on dashcam and satellite imagery.

Keywords

  • Cross-view Image Matching
  • Cyber-Resilient Vehicle Localization
  • Dashcam-Satellite Fusion
  • Image Retrieval

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Software
  • Theoretical Computer Science

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