236
P. Drap et al.
In this case, both of the survey see the more or less the same part of the site, the
only big difference between them is the resolution and so, the general accuracy.
Merging photogrammetric data on the full acoustic model was done with an RMS
of 0.032 m.
We are still working on merging partial photogrammetric survey on acoustic data
in an automatic way.
14.5 Conclusion
The ROV3D is an ambitious project, partially funded by the European Regional
Development Fund and the French Single Inter-Ministry Fund (FUI) for funding research involving both academic laboratories and industry and also by French regional
structure as “Conseil Régional PACA”, “Conseil Général des Bouches du Rhˆ one”
and “Marseille Provence Métropole”. It takes benefit from a strong collaboration
between a research laboratory and two private companies in order to be able to test
and improve methods and algorithms.
The project aims to produce a complete set of tools and methods for underwater
survey in complex and varied environment, for example, real 3D sites as caves,
wrecks, walls where a simple type of terrain modelling as DTM is not enough.
Moreover the interest of this project is to produce accurate 3D models with texture
information and thanks to the combination between the acoustic and the optical
approaches developing specific image processing filters in order to correct photo
illumination in underwater conditions.
The project is now quite mature and close to be fully operational. We are still
working on marine integration in a small ROV and also on a real-time process in
order to have continuous feedback on-board of the survey performed by the ROV. A
draft mosaic and a 3D model can be computed on the fly using synchronized video
cameras. We are working on a hybrid system, merging high- and low-resolution
cameras in order to be able to process results in real-time as well as to be able to
process results off-line with a high quality, as presented in Sect. IV of this paper.
References
Agarwal S, Furukawa Y, Snavely N, Curless B, Seitz SM, Szeliski R (2010) Reconstructing Rome.
Computer 43:40–47 (isbn/issn:0018–9162)
Ahonen T, Hadid A, Pietikainen M (2006) Face description with local binary patterns: application
to face recognition. IEEE Trans Pattern Anal Mach Intell 28(12):2037–2041
Baluja S, Rowley HA (2005) Boosting sex identification performance. AAAI 1508–1513
Barazzetti L, Scaioni M, Remondino F (2010) Orientation and 3D modelling from markerless terrestrial images: combining accuracy with automation. Photogramm Rec 25:356–381 (Blackwell
Publishing Ltd(Pub.), isbn/issn:1477–9730).
Bay H, Ess A, Tuytelaars T, Van Gool L (2008) Speeded-up robust features (SURF). Comput Vis
Image Underst 110:346–359 (isbn/issn:1077–3142)
P. Drap et al.
In this case, both of the survey see the more or less the same part of the site, the
only big difference between them is the resolution and so, the general accuracy.
Merging photogrammetric data on the full acoustic model was done with an RMS
of 0.032 m.
We are still working on merging partial photogrammetric survey on acoustic data
in an automatic way.
14.5 Conclusion
The ROV3D is an ambitious project, partially funded by the European Regional
Development Fund and the French Single Inter-Ministry Fund (FUI) for funding research involving both academic laboratories and industry and also by French regional
structure as “Conseil Régional PACA”, “Conseil Général des Bouches du Rhˆ one”
and “Marseille Provence Métropole”. It takes benefit from a strong collaboration
between a research laboratory and two private companies in order to be able to test
and improve methods and algorithms.
The project aims to produce a complete set of tools and methods for underwater
survey in complex and varied environment, for example, real 3D sites as caves,
wrecks, walls where a simple type of terrain modelling as DTM is not enough.
Moreover the interest of this project is to produce accurate 3D models with texture
information and thanks to the combination between the acoustic and the optical
approaches developing specific image processing filters in order to correct photo
illumination in underwater conditions.
The project is now quite mature and close to be fully operational. We are still
working on marine integration in a small ROV and also on a real-time process in
order to have continuous feedback on-board of the survey performed by the ROV. A
draft mosaic and a 3D model can be computed on the fly using synchronized video
cameras. We are working on a hybrid system, merging high- and low-resolution
cameras in order to be able to process results in real-time as well as to be able to
process results off-line with a high quality, as presented in Sect. IV of this paper.
References
Agarwal S, Furukawa Y, Snavely N, Curless B, Seitz SM, Szeliski R (2010) Reconstructing Rome.
Computer 43:40–47 (isbn/issn:0018–9162)
Ahonen T, Hadid A, Pietikainen M (2006) Face description with local binary patterns: application
to face recognition. IEEE Trans Pattern Anal Mach Intell 28(12):2037–2041
Baluja S, Rowley HA (2005) Boosting sex identification performance. AAAI 1508–1513
Barazzetti L, Scaioni M, Remondino F (2010) Orientation and 3D modelling from markerless terrestrial images: combining accuracy with automation. Photogramm Rec 25:356–381 (Blackwell
Publishing Ltd(Pub.), isbn/issn:1477–9730).
Bay H, Ess A, Tuytelaars T, Van Gool L (2008) Speeded-up robust features (SURF). Comput Vis
Image Underst 110:346–359 (isbn/issn:1077–3142)