최근 교육, 제조, 건설 등 다양한 응용 분야에서 사실적인 가상환경을 표현하기 위하여 실세계 영상데이터를 활용하는 사례가 증가하고 있다. 특히, 스마트 시티 등 디지털 트윈에 대한 관심이 높아지면서, 항공 영상 등 실제 촬영한 영상을 이용하여 현실감 있는 3D 도시 모델을 구축하고 있다. 그러나, 촬영된 항공 영상에는 태양에 의한 그림자가 포함되어 있으며, 그림자가 포함된 3D 도시 모델은 사용자에게 정보를 왜곡시켜 표현하는 문제를 안고 있다. 그림자를 제거하기 위하여 그동안 많은 연구가 진행되었지만, 아직 까지 해결하기 어려운 도전적인 문제로 인식되고 있다. 본 논문에서는 VWorld에서 제공하는 3차원 공간정보를 이용하여 건물의 높이맵을 포함한 가상환경 데이터 셋을 구축하고, 높이맵과 딥러닝을 이용한 새로운 그림자 탐지 방법을 제안한다. 실험 결과에 의하면, 높이맵을 사용했을 때 기존 방법보다 그림자 탐지 에러율이 감소한 것을 확인할 수 있다.
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