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  • 1
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    Optical and hydroacoustical measurements of bubble-flow seepage offshore Oregon (~46° N) during RV FALKOR cruise FK190612 (2022)
    PANGAEA
    Details
    Publication Date: 2024-04-20
    Description: Two lander-based devices, the Bubble-Box and GasQuant-II, were used to investigate the spatial and temporal variability and total gas flow rates of a seep area offshore Oregon, United States. The Bubble-Box is a stereo camera–equipped lander that records bubbles inside a rising corridor with 80 Hz, allowing for automated image analyses of bubble size distributions and rising speeds. GasQuant is a hydroacoustic lander using a horizontally oriented multibeam swath (Imagenex DeltaT) to record the backscatter intensity of bubble streams passing the swath plain. The experimental set up at the Astoria Canyon site at a water depth of about 500m aimed at calibrating the hydroacoustic GasQuant data with the visual Bubble-Box data for a spatial and temporal flow rate quantification of the site. For about 90h in total, both systems were deployed simultaneously and pressure and temperature data were recorded using a CTD as well. The data presented here contain post-processed information collected with the two lander-based devices during the cruise FK190612 on board RV FALKOR from the Schmidt-Ocean Institute in June 2019 (https://schmidtocean.org/cruise/methane-seeps-at-edge-of-hydrate-stability/). The first dataset contains post-processed ASCII information of the optic data recorded with the Bubble-Box system during two deployments (BBM-11 and BBM-17) and includes overall results of bubble sizes, volumes, rising speeds and flow rates of the observed bubble streams. A second dataset contains the acoustic backscatter of a seep site collected with the GasQuant II system during two deployments (GQM-3 and GQM-4). Each file contains the uncalibrated backscatter averaged in time (1 minute average) of the original dataset recorded with the GasQuant II. Files are provided in the Imagenex DeltaT data output format (*.83b) and can be easily visualized and inspected using FMMidwater (QPS) .
    Keywords: Astoria canyon; Astoria Canyon, offshore Oregon; Binary Object; Binary Object (File Size); BMB; BubbleBox; Bubble monitoring box; Bubbles; Event label; Falkor; File content; FK190612; FK190612_BBM-11; FK190612_BBM-17; FK190612_GQM-3; FK190612_GQM-4; GASQUANT; Gas Quantification, Lander; GasQuant-II; GEOMAR; Helmholtz Centre for Ocean Research Kiel; Hydroacoustic quantification; Methane Seeps; optical bubble measurements
    Type: Dataset
    Format: text/tab-separated-values, 8 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 2
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    Adjustment and Calibration of Dome Port Camera Systems for Underwater Vision (2019)
    Springer
    In:  In: Pattern Recognition: 41st DAGM German Conference, DAGM GCPR 2019, Dortmund, Germany, September 10–13, 2019, Proceedings. , ed. by Fink, G. A., Frintrop, S. and Jiang, X. Lecture Notes in Computer Science, 11824 . Springer, Cham, pp. 79-92. ISBN 978-3-030-33676-9
    Details
    Publication Date: 2020-02-26
    Description: Dome ports act as spherical windows in underwater housings through which a camera can observe objects in the water. As compared to flat glass interfaces, they do not limit the field of view, and they do not cause refraction of light observed by a pinhole camera positioned exactly in the center of the dome. Mechanically adjusting a real lens to this position is a challenging task, in particular for those integrated in deep sea housings. In this contribution a mechanical adjustment procedure based on straight line observations above and below water is proposed that allows for accurate alignments. Additionally, we show a chessboard-based method employing an underwater/above-water image pair to estimate potentially remaining offsets from the dome center to allow refraction correction in photogrammetric applications. Besides providing intuition about the severity of refraction in certain settings, we demonstrate the methods on real data for acrylic and glass domes in the water.
    Type: Book chapter , NonPeerReviewed , info:eu-repo/semantics/bookPart
    Format: text
    DOI: 10.1007/978-3-030-33676-9_6
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    OceanRep: Book chapter
  • 3
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    Deep Sea Robotic Imaging Simulator (2021)
    Springer
    In:  In: Pattern Recognition. ICPR International Workshops and Challenges. , ed. by Del Bimbo, A., Cucchiara, R., Sclaroff, S., Farinella, G. M., Mei, T., Bertini, M., Escalante, H. J. and Vezzani, R. Springer, Cham, pp. 375-389.
    Details
    Publication Date: 2021-08-03
    Description: Nowadays underwater vision systems are being widely applied in ocean research. However, the largest portion of the ocean - the deep sea - still remains mostly unexplored. Only relatively few image sets have been taken from the deep sea due to the physical limitations caused by technical challenges and enormous costs. Deep sea images are very different from the images taken in shallow waters and this area did not get much attention from the community. The shortage of deep sea images and the corresponding ground truth data for evaluation and training is becoming a bottleneck for the development of underwater computer vision methods. Thus, this paper presents a physical model-based image simulation solution, which uses an in-air texture and depth information as inputs, to generate underwater image sequences taken by robots in deep ocean scenarios. Different from shallow water conditions, artificial illumination plays a vital role in deep sea image formation as it strongly affects the scene appearance. Our radiometric image formation model considers both attenuation and scattering effects with co-moving spotlights in the dark. By detailed analysis and evaluation of the underwater image formation model, we propose a 3D lookup table structure in combination with a novel rendering strategy to improve simulation performance. This enables us to integrate an interactive deep sea robotic vision simulation in the Unmanned Underwater Vehicles simulator. To inspire further deep sea vision research by the community, we release the source code of our deep sea image converter to the public (https://www.geomar.de/en/omv-research/robotic-imaging-simulator).
    Type: Book chapter , NonPeerReviewed
    Format: text
    DOI: 10.1007/978-3-030-68790-8_29
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    OceanRep: Book chapter
  • 4
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    Considering Spherical Refraction in Visual Ocean Gas Release Quantification (2020)
    IEEE
    In:  [Paper] In: 2020 International Conference on Computer Vision, Image and Deep Learning, CVIDL 2020, 10.07.2020, Chongqing; China . Proceedings - 2020 International Conference on Computer Vision, Image and Deep Learning ; pp. 64-69 .
    Details
    Publication Date: 2021-01-11
    Description: Compared to traditional gas flow quantification methods, the stereo vision system has some advantages. However, underwater vision systems usually suffer from light refraction which can degrade the measurement accuracy from images. Cameras centered in spherical glass housings, dome ports, can theoretically avoid refraction, but misalignments in the dome create even more complex refraction effects than cameras behind flat glass windows. This paper introduces the spherical refraction model into a stereo vision gas flow quantification system. Also, this paper adds some contributions to an existing bubble quantification workflow for bubble size histogram and bubble volume estimation. First, the spherical glass dome port and the light propagation are modeled, and then the camera system is calibrated via underwater/in-air image pairs. Afterwards, the Epipolar Geometry Constraint is used to optimize the bubble matching. For volume estimation, an ellipsoid triangulation method is employed to improve ellipsoidal volume estimation. According to the calibration experiments and control experiments, the results show that the stereo vision gas flow quantification system can produce the volume of gas release accurately, which satisfies the requirements of long-term gas release monitoring in marine science.
    Type: Conference or Workshop Item , NonPeerReviewed
    Format: text
    DOI: 10.1109/CVIDL51233.2020.00020
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    OceanRep: Conference paper
  • 5
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    Refractive Geometry for Underwater Domes (2021)
    arXiv
    In:  (Submitted) arXiv e-prints .
    Details
    Publication Date: 2021-11-24
    Description: Underwater cameras are typically placed behind glass windows to protect them from the water. Spherical glass, a dome port, is well suited for high water pressures at great depth, allows for a large field of view, and avoids refraction if a pinhole camera is positioned exactly at the sphere's center. Adjusting a real lens perfectly to the dome center is a challenging task, both in terms of how to actually guide the centering process (e.g. visual servoing) and how to measure the alignment quality, but also, how to mechanically perform the alignment. Consequently, such systems are prone to being decentered by some offset, leading to challenging refraction patterns at the sphere that invalidate the pinhole camera model. We show that the overall camera system becomes an axial camera, even for thick domes as used for deep sea exploration and provide a non-iterative way to compute the center of refraction without requiring knowledge of exact air, glass or water properties. We also analyze the refractive geometry at the sphere, looking at effects such as forward- vs. backward decentering, iso-refraction curves and obtain a 6th-degree polynomial equation for forward projection of 3D points in thin domes. We then propose a pure underwater calibration procedure to estimate the decentering from multiple images. This estimate can either be used during adjustment to guide the mechanical position of the lens, or can be considered in photogrammetric underwater applications.
    Type: Article , NonPeerReviewed , info:eu-repo/semantics/article
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Article in a Scientific Journal - without review
  • 6
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    MaCal – Macro Lens Calibration and the Focus Stack Camera Model (2021)
    In:  [Paper] In: 3DV 2021 International Conference on 3D Vision, 01.-03.12.2021, Online .
    Details
    Publication Date: 2022-01-14
    Description: Macro photography is characterized by a very shallow depth of field, which challenges classical structure from motion and even camera calibration techniques, since images suffer from large defocussed areas. Computational photography methods such as focus stacking combine the sharp areas of many photos into one, which can produce spectacular images of insects or small structures. In this contribution we analyse the camera model to describe such focus stacked images in photogrammetry and computer vision and derive a camera calibration pipeline for macro photography to enable photogrammetry and 3D reconstruction of tiny objects. We demonstrate the effectiveness of the approach on raytraced images with ground truth and real images.
    Type: Conference or Workshop Item , NonPeerReviewed , info:eu-repo/semantics/conferenceObject
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Conference paper
  • 7
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    In-Situ Joint Light and Medium Estimation for Underwater Color Restoration (2021)
    In:  [Paper] In: 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 11.-17.10.2021, Montreal, Canada .
    Details
    Publication Date: 2022-01-14
    Type: Conference or Workshop Item , NonPeerReviewed , info:eu-repo/semantics/conferenceObject
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Conference paper
  • 8
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    Refractive Geometry for Underwater Domes (2022)
    Elsevier
    Details
    Publication Date: 2024-02-07
    Description: Underwater cameras are typically placed behind glass windows to protect them from the water. Spherical glass, a dome port, is well suited for high water pressures at great depth, allows for a large field of view, and avoids refraction if a pinhole camera is positioned exactly at the sphere’s center. Adjusting a real lens perfectly to the dome center is a challenging task, both in terms of how to actually guide the centering process (e.g. visual servoing) and how to measure the alignment quality, but also, how to mechanically perform the alignment. Consequently, such systems are prone to being decentered by some offset, leading to challenging refraction patterns at the sphere that invalidate the pinhole camera model. We show that the overall camera system becomes an axial camera, even for thick domes as used for deep sea exploration and provide a non-iterative way to compute the center of refraction without requiring knowledge of exact air, glass or water properties. We also analyze the refractive geometry at the sphere, looking at effects such as forward- vs. backward decentering, iso-refraction curves and obtain a 6th-degree polynomial equation for forward projection of 3D points in thin domes. We then propose a pure underwater calibration procedure to estimate the decentering from multiple images. This estimate can either be used during adjustment to guide the mechanical position of the lens, or can be considered in photogrammetric underwater applications.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 9
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    Marine bubble flow quantification using wide-baseline stereo photogrammetry (2022)
    Elsevier
    Details
    Publication Date: 2024-02-07
    Description: Reliable quantification of natural and anthropogenic gas release (e.g. CO2, methane) from the seafloor into the water column, and potentially to the atmosphere, is a challenging task. While ship-based echo sounders such as single beam and multibeam systems allow detection of free gas, bubbles, in the water even from a great distance, exact quantification utilizing the hydroacoustic data requires additional parameters such as rise speed and bubble size distribution. Optical methods are complementary in the sense that they can provide high temporal and spatial resolution of single bubbles or bubble streams from close distance. In this contribution we introduce a complete instrument and evaluation method for optical bubble stream characterization targeted at flows of up to 100 ml/min and bubbles with a few millimeters radius. The dedicated instrument employs a high-speed deep sea capable stereo camera system that can record terabytes of bubble imagery when deployed at a seep site for later automated analysis. Bubble characteristics can be obtained for short sequences, then relocating the instrument to other locations, or in autonomous mode of definable intervals up to several days, in order to capture bubble flow variations due to e.g. tide dependent pressure changes or reservoir depletion. Beside reporting the steps to make bubble characterization robust and autonomous, we carefully evaluate the reachable accuracy to be in the range of 1–2% of the bubble radius and propose a novel auto-calibration procedure that, due to the lack of point correspondences, uses only the silhouettes of bubbles. The system has been operated successfully in 1000 m water depth at the Cascadia margin offshore Oregon to assess methane fluxes from various seep locations. Besides sample results we also report failure cases and lessons learnt during deployment and method development.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 10
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    Quantitatively Monitoring Bubble-Flow at a Seep Site Offshore Oregon: Field Trials and Methodological Advances for Parallel Optical and Hydroacoustical Measurements (2022)
    Frontiers
    Details
    Publication Date: 2024-02-07
    Description: Two lander-based devices, the Bubble-Box and GasQuant-II, were used to investigate the spatial and temporal variability and total gas flow rates of a seep area offshore Oregon, United States. The Bubble-Box is a stereo camera–equipped lander that records bubbles inside a rising corridor with 80 Hz, allowing for automated image analyses of bubble size distributions and rising speeds. GasQuant is a hydroacoustic lander using a horizontally oriented multibeam swath to record the backscatter intensity of bubble streams passing the swath plain. The experimental set up at the Astoria Canyon site at a water depth of about 500 m aimed at calibrating the hydroacoustic GasQuant data with the visual Bubble-Box data for a spatial and temporal flow rate quantification of the site. For about 90 h in total, both systems were deployed simultaneously and pressure and temperature data were recorded using a CTD as well. Detailed image analyses show a Gaussian-like bubble size distribution of bubbles with a radius of 0.6–6 mm (mean 2.5 mm, std. dev. 0.25 mm); this is very similar to other measurements reported in the literature. Rising speeds ranged from 15 to 37 cm/s between 1- and 5-mm bubble sizes and are thus, in parts, slightly faster than reported elsewhere. Bubble sizes and calculated flow rates are rather constant over time at the two monitored bubble streams. Flow rates of these individual bubble streams are in the range of 544–1,278 mm 3 /s. One Bubble-Box data set was used to calibrate the acoustic backscatter response of the GasQuant data, enabling us to calculate a flow rate of the ensonified seep area (∼1,700 m 2 ) that ranged from 4.98 to 8.33 L/min (5.38 × 10 6 to 9.01 × 10 6 CH 4 mol/year). Such flow rates are common for seep areas of similar size, and as such, this location is classified as a normally active seep area. For deriving these acoustically based flow rates, the detailed data pre-processing considered echogram gridding methods of the swath data and bubble responses at the respective water depth. The described method uses the inverse gas flow quantification approach and gives an in-depth example of the benefits of using acoustic and optical methods in tandem.
    Type: Article , PeerReviewed
    Format: text
    Format: video
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    Format: other
    Format: text
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    OceanRep: Article in a Scientific Journal - peer-reviewed
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