Resource Efficient Mountainous Skyline Extraction using Shallow Learning

@article{Ahmad2021ResourceEM,
  title={Resource Efficient Mountainous Skyline Extraction using Shallow Learning},
  author={Touqeer Ahmad and Ebrahim Emami and Martin Cad{\'i}k and George Bebis},
  journal={2021 International Joint Conference on Neural Networks (IJCNN)},
  year={2021},
  pages={1-9}
}
Skyline plays a pivotal role in mountainous visual geo-localization and localization/navigation of planetary rovers/UAVs and virtual/augmented reality applications. We present a novel mountainous skyline detection approach where we adapt a shallow learning approach to learn a set of filters to discriminate between edges belonging to sky-mountain boundary and others coming from different regions. Unlike earlier approaches, which either rely on extraction of explicit feature descriptors and their… Expand

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