Three-Dimensional Target Reconstruction From Multiple 2-D Forward-Scan Sonar Views by Space Carving

Murat D. Aykin, Shahriar Negahdaripour

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Building 3-D object models from 2-D images is a key capability for target classification and identification, reacquisition, and environmental mapping, among many applications in underwater with poor visibility. We present a novel approach in utilizing multiple 2-D forward-look sonar images from known sonar poses to localize an acoustically opaque target and reconstruct its 3-D shape. Based on projections onto various images, the 3-D space not occupied by an imaged target within the sonar field of view is sequentially carved out, leaving the remaining volume as the estimate of the 3-D object region. The estimation generally improves with information from new distinct views, and moreover with images acquired through sonar roll motions, rather than circumnavigating the target. Computer simulations allow assessing the convergence properties and performance of the approach for convex and concave polygons. Additionally, results from experiments with real images of amorphous coral rocks and a miniature wood table demonstrate performance in the 3-D modeling of small objects with varying reflectance properties.

Original languageEnglish (US)
Pages (from-to)574-589
Number of pages16
JournalIEEE Journal of Oceanic Engineering
Volume42
Issue number3
DOIs
StatePublished - Jul 1 2017

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Sonar
Visibility
Wood
Rocks
Computer simulation
Experiments

Keywords

  • 3-D modeling
  • forward scan sonar
  • object reconstruction
  • space carving
  • target identification

ASJC Scopus subject areas

  • Ocean Engineering
  • Mechanical Engineering
  • Electrical and Electronic Engineering

Cite this

Three-Dimensional Target Reconstruction From Multiple 2-D Forward-Scan Sonar Views by Space Carving. / Aykin, Murat D.; Negahdaripour, Shahriar.

In: IEEE Journal of Oceanic Engineering, Vol. 42, No. 3, 01.07.2017, p. 574-589.

Research output: Contribution to journalArticle

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