Retrieval-based Localization Based on Domain-invariant Feature Learning under Changing Environments

@article{Hu2019RetrievalbasedLB,
  title={Retrieval-based Localization Based on Domain-invariant Feature Learning under Changing Environments},
  author={Hanjiang Hu and Hesheng Wang and Zhe Liu and Chenguang Yang and Weidong Chen and Le Xie},
  journal={2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year={2019},
  pages={3684-3689}
}
  • Hanjiang Hu, Hesheng Wang, Le Xie
  • Published 23 September 2019
  • Computer Science
  • 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Visual localization is a crucial problem in mobile robotics and autonomous driving. One solution is to retrieve images with known pose from a database for the localization of query images. However, in environments with drastically varying conditions (e.g. illumination changes, seasons, occlusion, dynamic objects), retrieval-based localization is severely hampered and becomes a challenging problem. In this paper, a novel domain-invariant feature learning method (DIFL) is proposed based on… 

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