Point Cloud Estimation During Aerial-Aquatic Transition in Monocular Camera-Based Localization and Mapping

Abstract

This paper presents a multi-box interpolation method to estimate point clouds during aerial-aquatic transition. Our proposed method is developed based on an investigation of noise characteristics of aerial point clouds and aquatic point clouds. To evaluate the performance of realistic point cloud estimation, we compare the interpolation method with the Gaussian mixture method. We also investigate how single-box and multi-box approaches deal with noise in point cloud estimation. The simulation and the experimental results show that the estimated point cloud is accurate even when the aerial and aquatic point clouds contain noise. Also, the multi-box concept helps the algorithm to avoid taking unwanted noise into consideration when predicting point clouds.