A Horizon-Tracking Method for Shipboard Video Stabilization and Rectification

Schwendeman, Michael; Thomson, Jim

doi:10.1175/jtech-d-14-00047.1

Cited by 31 publications

(17 citation statements)

References 33 publications

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“…Data collected at 15 Hz were subsampled to 1 Hz for processing. The camera was stabilized mechanically by a pan and tilt, and images were further stabilized in processing with the horizon method of Schwendeman and Thomson (2015).…”

Section: Ice Fractionmentioning

confidence: 99%

Air-sea interactions in the marginal ice zone

Zippel

Thomson

2016

Elementa: Science of the Anthropocene

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The importance of waves in the Arctic Ocean has increased with the significant retreat of the seasonal sea-ice extent. Here, we use wind, wave, turbulence, and ice measurements to evaluate the response of the ocean surface to a given wind stress within the marginal ice zone, with a focus on the local wind input to waves and subsequent ocean surface turbulence. Observations are from the Beaufort Sea in the summer and early fall of 2014, with fractional ice cover of up to 50%. Observations showed strong damping and scattering of short waves, which, in turn, decreased the wind energy input to waves. Near-surface turbulent dissipation rates were also greatly reduced in partial ice cover. The reductions in waves and turbulence were balanced, suggesting that a wind-wave equilibrium is maintained in the marginal ice zone, though at levels much less than in open water. These results suggest that air-sea interactions are suppressed in the marginal ice zone relative to open ocean conditions at a given wind forcing, and this suppression may act as a feedback mechanism in expanding a persistent marginal ice zone throughout the Arctic.

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Section: Ice Fractionmentioning

confidence: 99%

Air-sea interactions in the marginal ice zone

Zippel

Thomson

2016

Elementa: Science of the Anthropocene

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“…Schwendeman, M., and J. Thomson (2015), Observations of whitecap coverage and the relation to wind stress, wave slope, and turbulent dissipation,…”

Section: Citationmentioning

confidence: 99%

Observations of whitecap coverage and the relation to wind stress, wave slope, and turbulent dissipation

Schwendeman

Thomson

2015

JGR Oceans

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Shipboard measurements of whitecap coverage are presented from two cruises in the North Pacific, and compared with in situ measurements of wind speed and friction velocity, average wave steepness, and near‐surface turbulent dissipation. A threshold power law fit is proposed for all variables, which incorporates the flexibility of a power law with the threshold behavior commonly seen in whitecapping. The fit of whitecap coverage to wind speed, U10, closely matches similar relations from three recent studies, particularly in the range of 6–14 m/s. At higher wind speeds, the whitecap coverage data level off relative to the fits, and an analysis of the residuals shows some evidence of reduced whitecapping in rapidly developing waves. Wave slope variables are examined for potential improvement over wind speed parameterizations. Of these variables, the mean square slope of the equilibrium range waves has the best statistics, which are further improved after normalizing by the directional spread and frequency bandwidth. Finally, the whitecap coverage is compared to measurements of turbulent dissipation. Though still statistically significant, the correlation is worse than the wind or wave relations, and residuals show a strong negative trend with wave age. This may be due to an increased influence of microbreaking in older wind seas.

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“…However, in some cases, cameras just look at the ocean covering only a small beach portion, offering few or no fixed salient features. Some studies have overcome this limitation by tracking the horizon and using it as a geometric constraint in order to estimate the camera position and stabilize the images [33,34]. On the other hand, anticipating or predicting the movement of a camera can also be considered as an alternative approximation to reduce image deviation after acquisition when no features are available in the camera view field.…”

Section: Introductionmentioning

confidence: 99%

A Simple and Efficient Image Stabilization Method for Coastal Monitoring Video Systems

et al. 2019

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Fixed video camera systems are consistently prone to importune motions over time due to either thermal effects or mechanical factors. Even subtle displacements are mostly overlooked or ignored, although they can lead to large geo-rectification errors. This paper describes a simple and efficient method to stabilize an either continuous or sub-sampled image sequence based on feature matching and sub-pixel cross-correlation techniques. The method requires the presence and identification of different land-sub-image regions containing static recognizable features, such as corners or salient points, referred to as keypoints. A Canny edge detector ( C E D ) is used to locate and extract the boundaries of the features. Keypoints are matched against themselves after computing their two-dimensional displacement with respect to a reference frame. Pairs of keypoints are subsequently used as control points to fit a geometric transformation in order to align the whole frame with the reference image. The stabilization method is applied to five years of daily images collected from a three-camera permanent video system located at Anglet Beach in southwestern France. Azimuth, tilt, and roll deviations are computed for each camera. The three cameras showed motions on a wide range of time scales, with a prominent annual signal in azimuth and tilt deviation. Camera movement amplitude reached up to 10 pixels in azimuth, 30 pixels in tilt, and 0.4° in roll, together with a quasi-steady counter-clockwise trend over the five-year time series. Moreover, camera viewing angle deviations were found to induce large rectification errors of up to 400 m at a distance of 2.5 km from the camera. The mean shoreline apparent position was also affected by an approximately 10–20 m bias during the 2013/2014 outstanding winter period. The stabilization semi-automatic method successfully corrects camera geometry for fixed video monitoring systems and is able to process at least 90% of the frames without user assistance. The use of the C E D greatly improves the performance of the cross-correlation algorithm by making it more robust against contrast and brightness variations between frames. The method appears as a promising tool for other coastal imaging applications such as removal of undesired high-frequency movements of cameras equipped in unmanned aerial vehicles (UAVs).

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A Horizon-Tracking Method for Shipboard Video Stabilization and Rectification

Cited by 31 publications

References 33 publications

Air-sea interactions in the marginal ice zone

Air-sea interactions in the marginal ice zone

Observations of whitecap coverage and the relation to wind stress, wave slope, and turbulent dissipation

A Simple and Efficient Image Stabilization Method for Coastal Monitoring Video Systems

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