Remote sensing using laser projection photogrammetry for underwater surveys

Kocak, Donna M.; Jagielo, Thomas H.; Wallace, Farron; Kloske, John

doi:10.1109/igarss.2004.1368693

Cited by 9 publications

(10 citation statements)

References 2 publications

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“…Furthermore, piloting was influenced by the topography, leading to shorter subtransects modelled in Chile due to abrupt camera movements. Overall, the accuracy of the models presented in this study was acceptable and comparable to results obtained from perspective grids (Smith and Hamilton, 1983;Kocak et al, 2004). The distortion of the reference scales due to substrate roughness in Chile was identified as the main source of imprecision.…”

Section: Photomodelersupporting

confidence: 72%

“…The choice of the geographic coordinate system can greatly impact the results as an inadequate projection would lead to high distortions, especially in polar regions (Sievers and Bennat, 1989). Transect length might also be evaluated from the speed recorded by a Doppler velocity log (DVL) (Pinkard et al, 2005;Snyder, 2010;Stierhoff et al, 2012) or read directly from the DVL bottom track data (Kocak et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

“…Other means have been suggested for area determination, e.g. measuring distances between features on bathymetric charts (Karpov et al, 2006), flying over a known length of tether from a weight (Auster et al, 1989), using a weighted wheel bound to an odometer (Pollio, 1969), deploying a scale (Patterson et al, 2009), frames (Kocak et al, 2004;Amado-Filho et al, 2012) or using objects of known size as scaling references (Jones et al, 2006(Jones et al, , 2009.…”

Section: Introductionmentioning

confidence: 99%

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A new 3-D-modelling method to extract subtransect dimensions from underwater videos

Fillinger¹,

Funke²

2012

Preprint

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Underwater video transects have become a common tool for quantitative analysis of the seafloor. However a major difficulty remains in the accurate determination of the area surveyed as underwater navigation can be unreliable and image scaling does not always compensate for distortions due to perspective and topography. Depending on the camera setup and available instruments, different methods of surface measurement are applied which make it difficult to compare data obtained by different vehicles. 3-D modelling of the seafloor based on 2-D video data and a reference scale can be used to compute subtransects dimensions. Focussing on the length of the subtransect, the data obtained from 3-D models created with the software PhotoModeler Scanner are compared with those determined from underwater acoustic positioning (Ultra-Short BaseLine – USBL) and bottom tracking (Doppler Velocity Log – DVL). 3-D models building and scaling was successfully conducted on all three tested setups while the distortion of the reference scales due to substrate roughness was identified as the main source of imprecision. Acoustic positioning was generally inaccurate and DVL unreliable on rough terrain. Subtransect lengths assessed with PhotoModeler were on average 20% longer than those derived from the USBL due to the higher spatial resolution and the inclusion of slope. On a high relief wall, DVL and 3-D modelling yielded similar results. At present, 3-D modelling is the most powerful, albeit the most time-consuming, method for the accurate determination of video subtransect dimensions

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Section: Photomodelersupporting

confidence: 72%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A new 3-D-modelling method to extract subtransect dimensions from underwater videos

Fillinger¹,

Funke²

2012

Preprint

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“…In 2002, the WDFW used the manned submersible DSV Delta (Delta Oceanographics) to conduct sea-trials of a 3-beam laser system designed to improve the accuracy of density estimates obtained from in situ video surveys (Kocak et al 2004). The system incorporates two lasers mounted in parallel with a third laser crossing at an oblique angle through the parallel beams.…”

Section: Technological Improvementsmentioning

confidence: 99%

Conducting Visual Surveys with a Small ROV in Shallow Water

Pacunski¹,

Palsson²,

Greene³

et al. 2008

Marine Habitat Mapping Technology for Alaska

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Small remotely operated vehicles (ROVs), sometimes described as low-cost (<$150,000) ROVs, have become valuable tools in the study of marine organisms and their habitats. The versatility and relative simplicity of these vehicles is enabling scientists and fishery managers to develop a better understanding of the marine ecosystem that has not been possible using conventional survey methodologies. The ability to work at depths beyond the reach of scuba divers and in complex habitats inaccessible to trawl surveys is helping to "fill the information gap" between nearshore and deep offshore habitats, allowing for the development of more comprehensive management strategies of the ocean's resources.Small ROVs are especially suited for use by natural resource agencies and academic institutions operating on limited budgets with minimal resources. In calm, nearshore conditions, a small ROV can be operated from vessels as small as 6 m with a minimum of equipment and crew. In contrast, conducting safe, quantitative surveys with a small ROV in more extreme marine environments increases the complexity of the operation and requires additional equipment and personnel to ensure success. This paper focuses on the technical aspects of designing and conducting shallow-water (<200 m) surveys with a small ROV, based on our experience using a Deep Ocean Engineering Phantom HD2+2 ROV in San Juan Channel, Washington. Topics addressed include equipment, navigation and tracking, deployment protocols, tether management, camera calibration, survey design, data collection, hazards and safety, transect length and width, and recent technological developments.

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“…Distance between the camera and seafloor is uniquely identified by a distance between a laser dot and a vanishing point (or equivalently, a distance between laser dots). Recent advances in using this technology are described in [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

UVSD: Software for Detection of Color Underwater Features

Rzhanov

Mamaenko

Yoklavich

Proceedings of OCEANS 2005 MTS/IEEE

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-Underwater Video Spot Detector (UVSD) is a software package designed to analyze underwater video for continuous spatial measurements (path traveled, distance to the bottom, roughness of the surface etc.)Laser beams of known geometry are often used in underwater imagery to estimate the distance to the bottom. This estimation is based on the manual detection of laser spots which is labor intensive and time consuming so usually only a few frames can be processed this way. This allows for spatial measurements on single frames (distance to the bottom, size of objects on the sea-bottom), but not for the whole video transect.We propose algorithms and a software package implementing them for the semi-automatic detection of laser spots throughout a video which can significantly increase the effectiveness of spatial measurements. The algorithm for spot detection is based on the Support Vector Machines approach to Artificial Intelligence. The user is only required to specify on certain frames the points he or she thinks are laser dots (to train an SVM model), and then this model is used by the program to detect the laser dots on the rest of the video.As a result the precise (precision is only limited by quality of the video) spatial scale is set up for every frame. This can be used to improve video mosaics of the sea-bottom. The temporal correlation between spot movements changes and their shape provides the information about sediment roughness. Simultaneous spot movements indicate changing distance to the bottom; while uncorrelated changes indicate small local bumps.UVSD can be applied to quickly identify and quantify seafloor habitat patches, help visualize habitats and benthic organisms within large-scale landscapes, and estimate transect length and area surveyed along video transects.

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Remote sensing using laser projection photogrammetry for underwater surveys

Cited by 9 publications

References 2 publications

A new 3-D-modelling method to extract subtransect dimensions from underwater videos

A new 3-D-modelling method to extract subtransect dimensions from underwater videos

Conducting Visual Surveys with a Small ROV in Shallow Water

UVSD: Software for Detection of Color Underwater Features

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