Applying Gaussian Mixture Models to Detect Fish from Airborne LiDAR Measurements

Scofield, Trey P.; Belfort, Jackson; Churnside, James H.; Roddewig, Michael R.; Shaw, Joseph A.; Whitaker, Bradley M.

doi:10.1109/rapid51799.2021.9521457

Cited by 2 publications

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The former is already known in hydraulics as one of the innovative ways to calculate flow velocities from video footages. The latter is generally known in moving object recognition (video surveillance systems and traffic control), but it is not widely known in hydraulics so far (the exceptions are focusing on fish monitoring, e.g., Huang et al 2015;Scofield et al 2021). We name the new method Video-based Bedload Tracker (VBT).…”

Section: Methodsmentioning

confidence: 99%

Bedload transport analysis using image processing techniques

et al. 2022

View full text Add to dashboard Cite

Bedload transport is an important factor to describe the hydromorphological processes of fluvial systems. However, conventional bedload sampling methods have large uncertainty, making it harder to understand this notoriously complex phenomenon. In this study, a novel, image-based approach, the Video-based Bedload Tracker (VBT), is implemented to quantify gravel bedload transport by combining two different techniques: Statistical Background Model and Large-Scale Particle Image Velocimetry. For testing purposes, we use underwater videos, captured in a laboratory flume, with future field adaptation as an overall goal. VBT offers a full statistics of the individual velocity and grainsize data for the moving particles. The paper introduces the testing of the method which requires minimal preprocessing (a simple and quick 2D Gaussian filter) to retrieve and calculate bedload transport rate. A detailed sensitivity analysis is also carried out to introduce the parameters of the method, during which it was found that by simply relying on literature and the visual evaluation of the resulting segmented videos, it is simple to set them to the correct values. Practical aspects of the applicability of VBT in the field are also discussed and a statistical filter, accounting for the suspended sediment and air bubbles, is provided.

show abstract

Section: Methodsmentioning

confidence: 99%

Bedload transport analysis using image processing techniques

et al. 2022

View full text Add to dashboard Cite

show abstract

Review of airborne oceanic lidar remote sensing

Chen,

Zhang

et al. 2023

Intell. Mar. Technol. Syst.

View full text Add to dashboard Cite

Airborne oceanic lidars act as an active remote sensing technique have been proved to be one of the most effective and reliable means of oceanic profile remote sensing. This review aims to provide a comprehensive overview of the principles, methodologies, applications, and prospects of oceanic lidar remote sensing. A survey of the previous studies and works related to these techniques is presented in this paper, emphasizing the different mechanism in system design as well as data processing algorithms and their applications in the remote sensing of oceanic environmental parameters. The airborne lidar systems with multi-channels are designed to significantly improve the data quality and resolution of oceanic biological and geographic profiles. Algorithms for biological product retrieval and simulation based on typical radiation transfer models are described here to stimulate future research into ocean biogeochemistry. The advancement of airborne lidar applications in the near future is also presented.

show abstract

Applying Gaussian Mixture Models to Detect Fish from Airborne LiDAR Measurements

Cited by 2 publications

References 5 publications

Bedload transport analysis using image processing techniques

Bedload transport analysis using image processing techniques

Review of airborne oceanic lidar remote sensing

Contact Info

Product

Resources

About