3D reconstruction of line features using multi-view acoustic images in underwater environment

Ngoc Trung Mai, Hanwool Woo, Yonghoon Ji, Yusuke Tamura, Atsushi Yamashita, Hajime Asama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

In order to understand the underwater environment, it is essential to use sensing methodologies able to perceive the three dimensional (3D) information of the explored site. Sonar sensors are commonly employed in underwater exploration. This paper presents a novel methodology able to retrieve 3D information of underwater objects. The proposed solution employs an acoustic camera, which represents the next generation of sonar sensors, to extract and track the line of the underwater objects which are used as visual features for the image processing algorithm. In this work, we concentrate on artificial underwater environments, such as dams and bridges. In these structured environments, the line segments are preferred over the points feature, as they can represent structure information more effectively. We also developed a method for automatic extraction and correspondences matching of line features. Our approach enables 3D measurement of underwater objects using arbitrary viewpoints based on an extended Kalman filter (EKF). The probabilistic method allows computing the 3D reconstruction of underwater objects even in presence of uncertainty in the control input of the camera's movements. Experiments have been performed in real environments. Results showed the effectiveness and accuracy of the proposed solution.

Original languageEnglish
Title of host publicationMFI 2017 - 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages312-317
Number of pages6
ISBN (Electronic)9781509060641
DOIs
Publication statusPublished - 2017 Dec 7
Externally publishedYes
Event13th IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2017 - Daegu, Korea, Republic of
Duration: 2017 Nov 162017 Nov 18

Publication series

NameIEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
Volume2017-November

Conference

Conference13th IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2017
Country/TerritoryKorea, Republic of
CityDaegu
Period17/11/1617/11/18

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Science Applications

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