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의미론적 분할된 항공 사진을 활용한 영상 기반 항법

Vision-based Navigation using Semantically Segmented Aerial Images

  • 투고 : 2020.07.20
  • 심사 : 2020.09.14
  • 발행 : 2020.10.01

초록

영상 기반 항법은 GPS/INS 통합 항법 시스템의 취약점을 보강할 수 있는 보조 항법 기술로 비행체에서 촬영한 항공 영상과 기존의 데이터베이스를 비교하여 비행체의 위치를 구한다. 하지만 데이터베이스가 생성된 시점은 항공 영상 촬영 시점과 다를 수밖에 없으며, 이러한 시점 차이로 인해 두 영상 간의 다른 특징점들이 생성된다. 즉, 유사하지만 다른 두 영상이므로 일반적인 영상 대조 알고리즘을 항법 문제에 적용하기 힘들다. 따라서 본 논문에서는 인공지능 기법인 의미론적 분할을 활용하여 항공 영상에서 항법에 필요한 정보를 분류한 후 영상 대조를 수행하는 방법을 제안한다. 의미론적 분할로 시점 변화, 촬영 조건 변화가 있더라도 강건하게 두 영상이 정합 되도록 한다. 제안한 방법은 시뮬레이션과 비행 실험을 통해 성능을 확인하며, 일반적인 영상 대조 알고리즘을 이용하여 항법을 수행한 결과와 비교한다.

This paper proposes a new method for vision-based navigation using semantically segmented aerial images. Vision-based navigation can reinforce the vulnerability of the GPS/INS integrated navigation system. However, due to the visual and temporal difference between the aerial image and the database image, the existing image matching algorithms have difficulties being applied to aerial navigation problems. For this reason, this paper proposes a suitable matching method for the flight composed of navigational feature extraction through semantic segmentation followed by template matching. The proposed method shows excellent performance in simulation and even flight situations.

키워드

참고문헌

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