상세정보
학술지
Reflective Noise Filtering of Large-Scale Point Cloud Using Multi-Position LiDAR Sensing Data
- 저자
- Rui Gao, 박지선, Xiaohang Hu, 양승준, 조경은
- 발행일
- 202108
- 출처
- Remote Sensing, v.13 no.16, pp.1-22
- ISSN
- 2072-4292
- 출판사
- MDPI
- 협약과제
- 20ZH1200, 초실감 입체공간 미디어·콘텐츠 원천기술연구, 이태진
- 초록
- Signals, such as point clouds captured by light detection and ranging sensors, are often affected by highly reflective objects, including specular opaque and transparent materials, such as glass, mirrors, and polished metal, which produce reflection artifacts, thereby degrading the performance of associated computer vision techniques. In traditional noise filtering methods for point clouds, noise is detected by considering the distribution of the neighboring points. However, noise generated by reflected areas is quite dense and cannot be removed by considering the point distribution. Therefore, this paper proposes a noise removal method to detect dense noise points caused by reflected objects using multi-position sensing data comparison. The proposed method is divided into three steps. First, the point cloud data are converted to range images of depth and reflective intensity. Second, the reflected area is detected using a sliding window on two converted range images. Finally, noise is filtered by comparing it with the neighbor sensor data between the detected reflected areas. Experiment results demonstrate that, unlike conventional methods, the proposed method can better filter dense and large-scale noise caused by reflective objects. In future work, we will attempt to add the RGB image to improve the accuracy of noise detection.
- KSP 제안 키워드
- Computer Vision(CV), Conventional methods, Data comparison, Experiment results, Filtering method, Large-scale point cloud, Light detection and Ranging(LiDAR), Neighboring points, Noise Removal, Noise filtering, Point Cloud Data
본 저작물은 크리에이티브 커먼즈 저작자 표시 (CC BY) 조건에 따라 이용할 수 있습니다.
