I. Jeon, I. Lee

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations


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.

Original languageEnglish
Pages (from-to)957-962
Number of pages6
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Issue numberB2
StatePublished - 6 Aug 2020
Event2020 24th ISPRS Congress - Technical Commission II - Nice, Virtual, France
Duration: 31 Aug 20202 Sep 2020


  • 3D Reconstruction
  • SfM
  • Underwater Photogrammetry
  • Underwater SLAM
  • Visual SLAM


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