A Comparison of Image Based 3D Recovery Methods for Underwater Inspections - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2014

A Comparison of Image Based 3D Recovery Methods for Underwater Inspections


Offshore structures can be subjected to millions of variable amplitude load cycles during their service life which is the primary cause of structural deterioration. Such fatigue loading is exacerbated by marine growth colonization which changes the surface roughness characteristics and increases the diameter of structural members. Having an accurate knowledge of these parameters is essential for analyzing the increased hydrodynamic forces acting on the structure. This paper addresses the issue of acquiring shape information by comparing two popular classes of image based shape recovery techniques, stereo photography and Structure from Motion (SfM). Stereo photography utilises a dual camera set-up to simultaneously photograph an object of interest from slightly different viewpoints, whilst SfM methods generally involve a single camera moving in a static scene. In this paper, these techniques are performed on a controlled shape in an underwater setting, as well as synthetic data which allows for an irregular shape typical of marine growth to be tested whilst still having knowledge of the exact geometrical shape. The results reveal that the self-calibrated stereo approach fared well at getting an appropriately scaled full metric reconstruction, whilst the SfM approach was more susceptible to breaking down.
Fichier principal
Vignette du fichier
0241.pdf (638.84 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01020414 , version 1 (08-07-2014)


  • HAL Id : hal-01020414 , version 1


Michael O'Byrne, Vikram Pakrashi, Franck Schoefs, Bidisha Ghosh. A Comparison of Image Based 3D Recovery Methods for Underwater Inspections. EWSHM - 7th European Workshop on Structural Health Monitoring, IFFSTTAR, Inria, Université de Nantes, Jul 2014, Nantes, France. ⟨hal-01020414⟩
406 View
386 Download


Gmail Facebook X LinkedIn More