Wavelet-Based Optical Flow Estimation of Instant Surface Currents From Shore-Based and UAV Videos

Dérian, Pierre; Almar, Rafaël

doi:10.1109/tgrs.2017.2714202

Cited by 44 publications

(33 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This approach has observed both swash (Holland et al, 2001) and surf zone current velocity fields (Puleo et al, 2003). More recently a similar approach known as optical flow estimation has observed flow fields in the surf zone with some skill compared to in situ observations (Derian and Almar, 2017).…”

Section: Hydrodynamicsmentioning

confidence: 99%

WebCAT: Piloting the Development of a Web Camera Coastal Observing Network for Diverse Applications

Dusek

Hernandez

Willis³

et al. 2019

Front. Mar. Sci.

View full text Add to dashboard Cite

Web cameras are transforming coastal environmental monitoring. Improvements in camera technology and image processing capabilities, paired with decreases in cost, enable widespread use of camera systems by researchers, managers and first responders for a growing range of environmental monitoring applications. Applications are related to transportation and commerce, preparedness, risk reduction and response, and stewardship of coastal resources. While web cameras are seemingly ubiquitous, operators often follow unique installation procedures and collect, store, and process imagery data in various ways. These inconsistencies significantly limit the ability for imagery data to be shared and utilized across research and operational disciplines. Similar to the early days of other remote sensing networks like High Frequency Radar, the benefits and downstream application of coastal imagery data can be greatly enhanced through centralized data access and standardization of data collection, analysis and dissemination. The NOAA National Ocean Service Web Camera Applications Testbed (WebCAT) was launched in 2017 in partnership with SECOORA, as a public-private partnership to address this coastal ocean observing standardization need. WebCAT is a pilot project relying on the private sector expertise of Surfline, Inc., to install and operate several web cameras capable of meeting the short-term needs of diverse users including NOAA, USGS, state health agencies, academia and others. The project aims to determine operational imagery collection, storage, processing, access, and archival requirements that will foster collaboration across research and operational user communities. Seven web cameras have been installed at six locations along the southeast United States coast (from Florida to North Carolina) for purposes including: counting animals on the beach and migrating right whales, identifying rip currents, validating wave runup models, and understanding human use of natural resources. Here we present a review of the state of coastal imagery data and an overview of the WebCAT project. Goals of an upcoming community workshop will also be presented along with our vision for how WebCAT can motivate a future sustained operational web camera network.

show abstract

Section: Hydrodynamicsmentioning

confidence: 99%

WebCAT: Piloting the Development of a Web Camera Coastal Observing Network for Diverse Applications

Dusek

Hernandez

Willis³

et al. 2019

Front. Mar. Sci.

View full text Add to dashboard Cite

show abstract

“…Instantaneous velocities have also been calculated using particle image velocimetry (PIV), which tracks movement between two successive images by performing correlations of many small independent image segments [15][16][17][18][19]. Similarly, global formulations known as dense optical flow approaches can solve for the entire flow field simultaneously by minimizing a predefined function between two or more successive frames [20].…”

Section: Introductionmentioning

confidence: 99%

“…Each of these quantitative algorithms typically performs better with high-frequency, high-resolution images as input. Multiple images per second (>2 Hz) at small pixel sizes (<0.5 m) are common in previous efforts [16,17,20]. Two drawbacks arise from such approaches; large data files are created (multiple gigabytes) that negate longterm monitoring, and the currents resolved include short-term foam behavior not coherent with wave-averaged motions.…”

Section: Introductionmentioning

confidence: 99%

“…Present methods derived from high frame rates thus attempt to resolve a noisy surface expression of turbulent structures, generating, collecting, and advecting foam superimposed on wave-averaged flow patterns. Although present techniques can filter, average, and smooth velocities to retain realistic alongshore flows [13,17,20], the data file sizes and associated computing power necessary for processing prohibits continuous monitoring, timely assimilation to now-cast hydrodynamic models, and real-time early warning systems of persistent and transient rip currents. The objectives of this work are (1) to define an alternate approach, referred to henceforth as WAMFlow, to remotely derive flow features at spatial and temporal scales larger than turbulent structures associated with individual waves (Section 2), (2) to validate the method with drifter deployments that contextualize the spatial variability in flow (Section 3), and (3) to highlight the potential for the technique to contribute new insights to surf zone hydrodynamics (Section 4).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Quantifying Optically Derived Two-Dimensional Wave-Averaged Currents in the Surf Zone

et al. 2021

View full text Add to dashboard Cite

Complex two-dimensional nearshore current patterns are generated by feedbacks between sub-aqueous morphology and momentum imparted on the water column by breaking waves, winds, and tides. These non-stationary features, such as rip currents and circulation cells, respond to changing environmental conditions and underlying morphology. However, using fixed instruments to observe nearshore currents is limiting due to the high costs and logistics necessary to achieve adequate spatial sampling resolution. A new technique for processing surf-zone imagery, WAMFlow, quantifies fluid velocities to reveal complex, multi-scale (10 s–1000 s meters) nearshore surface circulation patterns. We apply the concept of a wave-averaged movie (WAM) to measure surf-zone circulation patterns on spatial scales of kilometers in the alongshore and 100 s of meters in the cross-shore. The approach uses a rolling average of 2 Hz optical imagery, removing the dominant optical clutter of incident waves, to leave the residual foam or water turbidity features carried by the flow. These residual features are tracked as quasi-passive tracers in space and time using optical flow, which solves for u and v as a function of image intensity gradients in x, y, and t. Surf zone drifters were deployed over multiple days with varying nearshore circulations to validate the optically derived flow patterns. Root mean square error are reduced to 0.1 m per second after filtering based on image attributes. The optically derived patterns captured longshore currents, rip currents, and gyres within the surf zone. Quantifying nearshore circulation patterns using low-cost image platforms and open-source computer vision algorithms presents the potential to further our understanding of fundamental surf zone dynamics.

show abstract

“…Compared to classical PIV, the optical flow approach led to results at higher spatial resolution even if longer computational times were required. In [42,43], global optical flow has been exploited to reconstruct instant surface currents from either satellite-or Unmanned Aerial Vehicle (UAV)-captured images.…”

Section: Introductionmentioning

confidence: 99%

Optical Tracking Velocimetry (OTV): Leveraging Optical Flow and Trajectory-Based Filtering for Surface Streamflow Observations

et al. 2018

View full text Add to dashboard Cite

Nonintrusive image-based methods have the potential to advance hydrological streamflow observations by providing spatially distributed data at high temporal resolution. Due to their simplicity, correlation-based approaches have until recent been preferred to alternative image-based approaches, such as optical flow, for camera-based surface flow velocity estimate. In this work, we introduce a novel optical flow scheme, optical tracking velocimetry (OTV), that entails automated feature detection, tracking through the differential sparse Lucas-Kanade algorithm, and then a posteriori filtering to retain only realistic trajectories that pertain to the transit of actual objects in the field of view. The method requires minimal input on the flow direction and camera orientation. Tested on two image data sets collected in diverse natural conditions, the approach proved suitable for rapid and accurate surface flow velocity estimations. Five different feature detectors were compared and the features from accelerated segment test (FAST) resulted in the best balance between the number of features identified and successfully tracked as well as computational efficiency. OTV was relatively insensitive to reduced image resolution but was impacted by acquisition frequencies lower than 7-8 Hz. Compared to traditional correlation-based techniques, OTV was less affected by noise and surface seeding. In addition, the scheme is foreseen to be applicable to real-time gauge-cam implementations.

show abstract

Wavelet-Based Optical Flow Estimation of Instant Surface Currents From Shore-Based and UAV Videos

Cited by 44 publications

References 31 publications

WebCAT: Piloting the Development of a Web Camera Coastal Observing Network for Diverse Applications

WebCAT: Piloting the Development of a Web Camera Coastal Observing Network for Diverse Applications

Quantifying Optically Derived Two-Dimensional Wave-Averaged Currents in the Surf Zone

Optical Tracking Velocimetry (OTV): Leveraging Optical Flow and Trajectory-Based Filtering for Surface Streamflow Observations

Contact Info

Product

Resources

About