Abstract
Abstract. The underwater environment has substantial properties for underwater research such as marine archaeology, monitoring coral reefs, and shipwrecks. SfM, as a major step of photogrammetry, has been widely used in the field. For a high 3D construction quality, images must have a clear visual sight environment and known orientations of the images. However, underwater images have various types of visual disturbances, but also GPS/INS, commonly used on the ground, are not accepted. Finding more feature points or using more images for SfM are solutions to the problems. However, these methods take high computational costs. An alternative to this problem is to provide the known orientations of the images. For a solution to provide known orientations of images, the presented method in this study uses visual SLAM that processes the localization of a vehicle system and mapping of surroundings. The experiment aims to verify whether SLAM improves the quality of underwater 3D reconstruction and the computation efficiency of SfM. We examine the two aqualoc datasets with the results of the number of cloud points, SfM processing time, and the number of matched images/total images and mean reprojection errors. The outcome shows SLAM-determined orientations improved the quality of 3D reconstruction and the computation efficiency of SfM with results of the increased number of point clouds and the decreased processing time.
Highlights
The underwater environment has substantial properties for underwater researches such as marine archaeology, monitoring coral reefs, and shipwrecks
A presented method in this paper aims to reconstruct an underwater environment by combining SfM with SLAMdetermined orientation
B are divided again according to the following conditions: the number of key point limit which means the upper limit of key points for each image, the number of images for the same video, and whether to process 3D reconstruction with the trajectory from visual SLAM
Summary
The underwater environment has substantial properties for underwater researches such as marine archaeology, monitoring coral reefs, and shipwrecks. In the second half of the twentieth century, AUVs (Autonomous Underwater Vehicles), USBL (Ultra-short Baseline), DVL (Doppler Velocity Log) are widely used for underwater researches, and they commonly exploited acoustic sensors such as sonar Due to their disadvantage of being expensive and large (), alternatives such as ROV (Remotely Operated Vehicle) with visual cameras, which are flexible, have been utilized (Teague & Scott, 2017). Backscattering that changes the direction of the light ray, turbidity from the cloudiness or haziness caused by large numbers of particles and dynamism from the motion of water are commonly shown in underwater images (Ferrera et al, 2019a). These obstructions can be major hindrances to 3D construction
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