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선박에서 증강현실 위치 정합 활용을 위한 기계학습 기반의 마커 복원 방법 연구
김영수(Youngsu Kim),이경호(Kyungho Lee),한영수(Young-Soo Han),여현빈(Hyunbin-Yeo) (사)한국CDE학회 2022 한국CDE학회 논문집 Vol.27 No.4
The interior of the ship is very complex and the equipment is equipped with pipes, valves, supports, etc. In order to utilize augmented reality in such an environment, it is more appropriate to use markers rather than markerless, which creates a model based on the characteristics of the target equipment. However, it is difficult to apply the marker because a lot of corrosion or damage to the marker may occur in the ship. Therefore, in this study, when a marker is damaged, it is intended to restore the marker using GAN among machine learning techniques. At this time, the model was built using the Pix2Pix, Cycle GAN, and Disco GAN algorithms widely used for images among GAN algorithms. Finally, an efficient marker restoration algorithm was verified by qualitatively and quantitatively comparing the model results.