A weighted KNN epipolar geometry-based approach for vision-based indoor localization using smartphone cameras

@article{Sadeghi2014AWK,
  title={A weighted KNN epipolar geometry-based approach for vision-based indoor localization using smartphone cameras},
  author={Hamed Sadeghi and Shahrokh Valaee and Shahram Shirani},
  journal={2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)},
  year={2014},
  pages={37-40}
}
We propose a weighted KNN Epipolar Geometry-based method for vision-based indoor localization using cellphone cameras. The proposed method is applicable for fine localization whenever a pose-tagged (position + rotation matrix) image database is available rather than just Geo-tagged one. To the best of our knowledge, this is the first that Epipolar geometry has been utilized for fine localization in indoor applications using smartphone images. We compare the performance of our method with two… CONTINUE READING
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