ORCID Profile
0000-0001-9416-5639
Current Organisation
University of Sydney
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Artificial Intelligence and Image Processing | Robotics And Mechatronics | Adaptive Agents and Intelligent Robotics | Pattern Recognition and Data Mining | Intelligent Robotics | Control Systems, Robotics and Automation | Image Processing | Special Vehicles | Marine Engineering | Maritime Engineering | Computer Vision | Ecological Impacts of Climate Change | Field robotics | Computer Vision | Machine learning | Ecology | Information Systems | Ocean Engineering | Computer vision | Natural Resource Management | Marine and Estuarine Ecology (incl. Marine Ichthyology) | Interorganisational Information Systems | Computer-Human Interaction | Environmental Impact Assessment | Mechanical Engineering | Marine And Estuarine Ecology (Incl. Marine Ichthyology) | Environmental Monitoring | Interdisciplinary Engineering | Life Histories (Incl. Population Ecology) | Sociobiology And Behavioural Ecology | Semi- and unsupervised learning | Simulation And Modelling | Ecological Applications | Knowledge Representation And Machine Learning | Infrastructure Engineering and Asset Management | Intelligent robotics | Biological Oceanography | Special Vehicles | Autonomous Vehicles | Interdisciplinary Engineering Not Elsewhere Classified | Film, Television and Digital Media | Landscape Ecology | Other Cinema And Electronic Arts | Ocean Engineering | Artificial intelligence | Data Communications |
ANZSRC Socio-Economic Objective (SEO)
Ecosystem Assessment and Management of Marine Environments | Integrated (ecosystem) assessment and management | Marine protected areas | Navy | Effects of Climate Change and Variability on Australia (excl. Social Impacts) | Command, Control and Communications | Navy | Integrated (ecosystem) assessment and management | Marine Flora, Fauna and Biodiversity | Information processing services | The creative arts | Integrated (ecosystem) assessment and management | Control of pests and exotic species | Oceanic processes (excl. climate related) | Physical and Chemical Conditions of Water in Coastal and Estuarine Environments | Information and Communication Services not elsewhere classified | Health not elsewhere classified | Computer hardware and electronic equipment not elsewhere classified | Expanding Knowledge in History and Archaeology | Transport not elsewhere classified | Oil and gas | Expanding Knowledge in Technology | Oil and Gas Exploration | Expanding Knowledge in the Environmental Sciences | Expanding Knowledge in Engineering | Expanding Knowledge in the Information and Computing Sciences | Other
Related Links
Publications
Estimation of clustering parameters using Gaussian process regression
Publisher: Public Library of Science (PLoS)
Date: 10-11-2014
Adaptive human sensor model in sensor networks
Publisher: IEEE
Date: 2005
Multi-Scale Measures of Rugosity, Slope and Aspect from Benthic Stereo Image Reconstructions
Publisher: Public Library of Science (PLoS)
Date: 12-12-2012
Terrain aided localisation and mapping for marine environments
Publisher: Springer Berlin Heidelberg
Date: 2006
DOI: 10.1007/11552246_11
Variability in mesophotic coral reef communities along the great barrier reef, Australia
Publisher: Inter-Research Science Center
Date: 03-05-2011
DOI: 10.3354/MEPS09046
Fish-Bird: Cross-disciplinary collaboration
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2008
DOI: 10.1109/MMUL.2008.7
Operators as information sources in sensor networks
Publisher: IEEE
Date: 2005
Multimodal information-theoretic measures for autonomous exploration
Publisher: IEEE
Date: 05-2016
Reconstructing pavlopetri: Mapping the world's oldest submerged town using stereo-vision
Publisher: IEEE
Date: 05-2011
Saliency ranking for benthic survey using underwater images
Publisher: IEEE
Date: 12-2010
Light field image denoising using a linear 4D frequency-hyperfan all-in-focus filter
Publisher: SPIE
Date: 14-02-2013
DOI: 10.1117/12.2002239
Multidimensional (MD) circuits and systems for emerging applications including cognitive radio, radio astronomy, robot vision and imaging
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2013
Rugosity, slope and aspect from bathymetric stereo image reconstructions
Publisher: IEEE
Date: 05-2010
A terrain-aided tracking algorithm for marine systems
Publisher: Springer Berlin Heidelberg
Date: 2006
DOI: 10.1007/10991459_10
Large-scale geographic variation in distribution and abundance of Australian deep-water kelp forests
Publisher: Public Library of Science (PLoS)
Date: 18-02-2015
Towards geo-referenced AUV navigation through fusion of USBL and DVL measurements
Publisher: IEEE
Date: 09-2006
Hierarchical Bayesian models for unsupervised scene understanding
Publisher: Elsevier BV
Date: 02-2015
Burnout and Work Engagement in Occupational Therapists
Publisher: SAGE Publications
Date: 03-2014
DOI: 10.4276/030802214X13941036266621
Abstract: Work engagement, characterized by vigour, dedication, and absorption, is often perceived as the opposite of burnout. Occupational therapists with burnout feel exhausted and disengaged from their work. This study aims to investigate demographic and work-related psychosocial factors associated with burnout and work engagement. A cross-sectional postal survey of 951 occupational therapists was conducted. Two models representing factors associated with burnout (F(15,871) = 28.01, p .001) and work engagement (F(10,852) = 16.15, p .001) accounted for 32.54% and 15.93% of the variance respectively. Burnout and work engagement were inversely associated (χ 2 (n = 941) = 55.16, p .001). Factors associated with burnout and work engagement were identified. The variables associated with burnout included: low psychological detachment from work during out-of-work hours, low income satisfaction, perceived work overload, difficulty saying ‘no’, 10 years' experience, low frequency of having a ‘belly laugh’, and not having children. High levels of work engagement were reported by therapists with the following: low psychological detachment from work, high income satisfaction, postgraduate qualifications, 40 hours work/week, high frequency of having a ‘belly laugh’, and having children. Understanding the factors associated with burnout and work engagement provides prerequisite information to inform strategies aimed at building healthy workforces.
Coregistered Hyperspectral and Stereo Image Seafloor Mapping from an Autonomous Underwater Vehicle
Publisher: Wiley
Date: 21-03-2018
DOI: 10.1002/ROB.21713
Convolutional neural networks for passive monitoring of a shallow water environment using a single sensor
Publisher: IEEE
Date: 03-2017
Parametric POMDPs for planning in continuous state spaces
Publisher: Elsevier BV
Date: 11-2006
Dynamic spectral-based underwater colour correction
Publisher: IEEE
Date: 06-2013
Go With the Flow: Energy Minimising Periodic Trajectories for UVMS
Publisher: IEEE
Date: 23-05-2022
Predictive habitat models from AUV-based multibeam and optical imagery
Publisher: IEEE
Date: 09-2010
Automated registration for multi-year robotic surveys of marine benthic habitats
Publisher: IEEE
Date: 11-2013
Towards component-based robotics
Publisher: IEEE
Date: 2005
Convolutional neural network for single-sensor acoustic localization of a transiting broadband source in very shallow water
Publisher: Acoustical Society of America (ASA)
Date: 12-2019
DOI: 10.1121/1.5138594
Abstract: When a broadband source of radiated noise transits past a fixed hydrophone, a Lloyd's mirror constructive/destructive interference pattern can be observed in the output spectrogram. By taking the spectrum of a (log) spectrum, the power cepstrum detects the periodic structure of the Lloyd's mirror fringe pattern by generating a sequence of pulses located at the fundamental quefrency and its multiples. The fundamental quefrency, which is the reciprocal of the frequency difference between adjacent destructive interference fringes, equates to the multipath delay time. An experiment is conducted where a motorboat transits past a hydrophone located about 1 m above the seafloor in very shallow water (20 m deep). The hydrophone has a frequency bandwidth of 90 kHz, and its output is s led at 250 kHz. A cepstrogram database is compiled from multiple vessel transits, and its cepstrum-based feature vectors (along with ground-truth range data) form the input to train a convolutional neural network (CNN) so that it can predict the source range relative to the hydrophone for other (“unseen”) vessel transits. The CNN provides an accurate prediction of the instantaneous source range even when the range estimate from conventional multipath passive ranging is biased, which occurs at low grazing angles (& °).
BioTIME: A database of biodiversity time series for the Anthropocene
Publisher: Wiley
Date: 07-2018
DOI: 10.1111/GEB.12729
Frequency-based underwater terrain segmentation
Publisher: Springer Science and Business Media LLC
Date: 27-07-2013
Crowdsourced saliency for mining robotically gathered 3D maps using multitouch interaction on smartphones and Tablets
Publisher: IEEE
Date: 05-2014
Special issue on robotics: Science and systems 2013
Publisher: SAGE Publications
Date: 08-2014
Classification with probabilistic targets
Publisher: IEEE
Date: 10-2012
Autonomous underwater navigation and control
Publisher: Cambridge University Press (CUP)
Date: 29-08-2001
DOI: 10.1017/S0263574701003423
Abstract: This paper describes the autonomous navigation and control of an undersea vehicle using a vehicle control architecture based on the Distributed Architeclure for Mobile Navigation and a terrain-aided navigation technique based on simultaneous localisation and map building. Development of the low-speed platform models for vehicle control and the theoretical and practical details of mapping and position estimation using sonar are provided. Details of an implementation of these techniques on a small submersible vehicle “Oberon” are presented.
Information based adaptive robotic exploration
Publisher: IEEE
Date: 2002
Mechanisms for haptic feedback
Publisher: IEEE
Date: 1995
Habitats and Benthos at Hydrographers Passage, Great Barrier Reef, Australia
Publisher: Elsevier
Date: 2012
Towards autonomous habitat classification using Gaussian mixture models
Publisher: IEEE
Date: 10-2010
A simple, fast, and repeatable survey method for underwater visual 3D benthic mapping and monitoring
Publisher: Wiley
Date: 15-02-2017
DOI: 10.1002/ECE3.2701
High resolution, consistent navigation and 3D optical reconstructions from AUVs using magnetic compasses and pressure-based depth sensors
Publisher: IEEE
Date: 05-2010
A behavior-based architecture for autonomous underwater exploration
Publisher: Elsevier BV
Date: 08-2002
Regional-scale benthic monitoring for Ecosystem-Based Fisheries Management (EBFM) using an Autonomous Underwater Vehicle (AUV)
Publisher: Oxford University Press (OUP)
Date: 18-05-2012
Abstract: Smale, D. A., Kendrick, G. A., Harvey, E. S., Langlois, T. J., Hovey, R. K., Van Niel, K. P., Waddington, K. I., Bellchambers, L. M., Pember, M. B., Babcock, R. C., Vanderklift, M. A., Thomson, D. P., Jakuba, M. V., Pizarro, O., and Williams, S. B. 2012. Regional-scale benthic monitoring for ecosystem-based fisheries management (EBFM) using an autonomous underwater vehicle (AUV). – ICES Journal of Marine Science, 69: 1108–1118. Monitoring marine habitats and bio ersity is critical for understanding ecological processes, conserving natural resources, and achieving ecosystem-based fisheries management (EBFM). Here, we describe the application of autonomous underwater vehicle (AUV) technology to conduct ongoing monitoring of benthic habitats at two key locations in Western Australia. Benthic assemblages on rocky reefs were s led with an AUV, which captured 000 geo-referenced images. Surveys were designed to obtain 100% coverage of 25 × 25 m patches of benthic habitat. In 2010, multiple patches were surveyed at 15–40-m depths at three reference sites at the Houtman Abrolhos Islands and at six reference sites at Rottnest Island. The following year, repeat surveys of the same geo-referenced patches were conducted. Benthic assemblages at the Houtman Abrolhos Islands were varied in that one reference site was dominated by hard corals, whereas the other two were macroalgae dominated. Conversely, assemblages at Rottnest Island were dominated by the kelp Ecklonia radiata. The AUV resurveyed each patch with high precision and demonstrated adequate power to detect change. Repeated observations at the reference sites will track natural variability in benthic habitat structure, which in turn will facilitate the detection of ecological change and ultimately feed back into EBFM processes.
Effective benthic surveying with autonomous underwater vehicles
Publisher: IEEE
Date: 09-2007
Return to antikythera: Multi-session SLAM based AUV mapping of a first century B.C. wreck site
Publisher: Springer International Publishing
Date: 2016
Anisotropic Disturbance Rejection for Kinematically Redundant Systems with Applications on an UVMS
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2021
Map management for efficient simultaneous localization and mapping (SLAM)
Publisher: Springer Science and Business Media LLC
Date: 2002
Generation and visualization of large-scale three-dimensional reconstructions from underwater robotic surveys
Publisher: Wiley
Date: 03-12-2010
DOI: 10.1002/ROB.20324
A benchmarking study on single image dehazing techniques for underwater autonomous vehicles
Publisher: IEEE
Date: 06-2017
Light Field Image Restoration for Vision in Scattering Media
Publisher: IEEE
Date: 10-2018
Automatic spectrometer/RGB camera spatial calibration
Publisher: IEEE
Date: 07-2013
Reflections on a decade of autonomous underwater vehicles operations for marine survey at the Australian Centre for Field Robotics
Publisher: Elsevier BV
Date: 2016
Characterization of measurement errors using structure-from-motion and photogrammetry to measure marine habitat structural complexity
Publisher: Wiley
Date: 15-06-2017
DOI: 10.1002/ECE3.3127
A Monte Carlo update for parametric POMDPs
Publisher: Springer Berlin Heidelberg
Date: 2010
Bundle adjustment in large-scale 3D reconstructions based on underwater robotic surveys
Publisher: IEEE
Date: 06-2011
Biometric assessment of deep-sea vent megabenthic communities using multi-resolution 3D image reconstructions
Publisher: Elsevier BV
Date: 10-2016
Robust broad-scale benthic habitat mapping when training data is scarce
Publisher: IEEE
Date: 05-2012
Recovering Depth from Still Images for Underwater Dehazing Using Deep Learning
Publisher: MDPI AG
Date: 15-08-2020
DOI: 10.3390/S20164580
Abstract: Estimating depth from a single image is a challenging problem, but it is also interesting due to the large amount of applications, such as underwater image dehazing. In this paper, a new perspective is provided by taking advantage of the underwater haze that may provide a strong cue to the depth of the scene, a neural network can be used to estimate it. Using this approach the depthmap can be used in a dehazing method to enhance the image and recover original colors, offering a better input to image recognition algorithms and, thus, improving the robot performance during vision-based tasks such as object detection and characterization of the seafloor. Experiments are conducted on different datasets that cover a wide variety of textures and conditions, while using a dense stereo depthmap as ground truth for training, validation and testing. The results show that the neural network outperforms other alternatives, such as the dark channel prior methods and it is able to accurately estimate depth from a single image after a training stage with depth information.
Spatially informed spectral unmixing
Publisher: IEEE
Date: 06-2015
Leveraging Metadata in Representation Learning with Georeferenced Seafloor Imagery
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2021
An efficient approach to bathymetric SLAM
Publisher: IEEE
Date: 10-2009
Multimodal learning and inference from visual and remotely sensed data
Publisher: SAGE Publications
Date: 14-12-2017
Abstract: Autonomous vehicles are often tasked to explore unseen environments, aiming to acquire and understand large amounts of visual image data and other sensory information. In such scenarios, remote sensing data may be available a priori, and can help to build a semantic model of the environment and plan future autonomous missions. In this paper, we introduce two multimodal learning algorithms to model the relationship between visual images taken by an autonomous underwater vehicle during a survey and remotely sensed acoustic bathymetry (ocean depth) data that is available prior to the survey. We present a multi-layer architecture to capture the joint distribution between the bathymetry and visual modalities. We then propose an extension based on gated feature learning models, which allows the model to cluster the input data in an unsupervised fashion and predict visual image features using just the ocean depth information. Our experiments demonstrate that multimodal learning improves semantic classification accuracy regardless of which modalities are available at classification time, allows for unsupervised clustering of either or both modalities, and can facilitate mission planning by enabling class-based or image-based queries.
GeoCLR: Georeference Contrastive Learning for Efficient Seafloor Image Interpretation
Publisher: Field Robotics Publication Society
Date: 10-03-2022
DOI: 10.55417/FR.2022037
Abstract: This paper describes georeference contrastive learning of visual representation (GeoCLR) for efficient training of deep-learning convolutional neural networks (CNNs). The method leverages georeference information by generating a similar image pair using images taken of nearby locations, and contrasting these with an image pair that is far apart. The underlying assumption is that images gathered within a close distance are more likely to have similar visual appearance, where this can be reasonably satisfied in seafloor robotic imaging applications where image footprints are limited to edge lengths of a few meters and are taken so that they overlap along a vehicle’s trajectory, whereas seafloor substrates and habitats have patch sizes that are far larger. A key advantage of this method is that it is self-supervised and does not require any human input for CNN training. The method is computationally efficient, where results can be generated between es during multi-day autonomous underwater vehicle (AUV) missions using computational resources that would be accessible during most oceanic field trials. We apply GeoCLR to habitat classification on a dataset that consists of ~86,000 images gathered using an AUV. We demonstrate how the latent representations generated by GeoCLR can be used to efficiently guide human annotation efforts, where the semi-supervised framework improves classification accuracy by an average of 10.2% compared to the state-of-the-art SimCLR using the same CNN and equivalent number of human annotations for training.
Bathymetric particle filter SLAM using trajectory maps
Publisher: SAGE Publications
Date: 11-09-2012
Abstract: We present an efficient and featureless approach to bathymetric simultaneous localization and mapping (SLAM) that utilizes a Rao–Blackwellized particle filter (RBPF) and Gaussian process (GP) regression to provide loop closures in areas with little to no overlap with previously explored terrain. To significantly reduce the memory requirements (thereby allowing for the processing of large datasets) a novel map representation is also introduced that, instead of directly storing estimates of seabed depth, records the trajectory of each particle and synchronizes them to a common log of bathymetric observations. Upon detecting a loop closure each particle is weighted by matching new observations to the current predictions generated from a local reconstruction of their map using GP regression. Here the spatial correlation in the environment is fully exploited, allowing predictions of seabed depth in areas that may not have been directly observed previously. The results demonstrate how observations of seafloor structure with partial overlap can be used by bathymetric SLAM to improve map self consistency when compared with dead reckoning fused with long-baseline (LBL) observations. In addition we show how mapping corrections can still be achieved even when no map overlap is present.
Topography, substratum and benthic macrofaunal relationships on a tropical mesophotic shelf margin, central Great Barrier Reef, Australia
Publisher: Springer Science and Business Media LLC
Date: 19-09-2011
Filling the gaps: Predicting the distribution of temperate reef biota using high resolution biological and acoustic data
Publisher: Elsevier BV
Date: 06-2014
Toward adaptive benthic habitat mapping using gaussian process classification
Publisher: Wiley
Date: 08-10-2010
DOI: 10.1002/ROB.20372
Improved Multipath Time Delay Estimation Using Cepstrum Subtraction
Publisher: IEEE
Date: 05-2019
Towards terrain-aided navigation for underwater robotics
Publisher: Informa UK Limited
Date: 2001
Adaptive exploration of benthic habitats using Gaussian processes
Publisher: IEEE
Date: 09-2010
Sound Source Localization in a Multipath Environment Using Convolutional Neural Networks
Publisher: IEEE
Date: 04-2018
An analysis of monochrome conversions and normalizations on the local binary patterns texture descriptors
Publisher: IEEE
Date: 12-2013
Towards image-based marine habitat classification
Publisher: IEEE
Date: 2008
Benthic monitoring with robotic platforms-The experience of Australia
Publisher: IEEE
Date: 03-2013
Linear volumetric focus for light field cameras
Publisher: Association for Computing Machinery (ACM)
Date: 02-03-2015
DOI: 10.1145/2665074
Abstract: We demonstrate that the redundant information in light field imagery allows volumetric focus, an improvement of signal quality that maintains focus over a controllable range of depths. To do this, we derive the frequency-domain region of support of the light field, finding it to be the 4D hyperfan at the intersection of a dual fan and a hypercone, and design a filter with correspondingly shaped passband. Drawing ex les from the Stanford Light Field Archive and images captured using a commercially available lenslet-based plenoptic camera, we demonstrate that the hyperfan outperforms competing methods including planar focus, fan-shaped antialiasing, and nonlinear image and video denoising techniques. We show the hyperfan preserves depth of field, making it a single-step all-in-focus denoising filter suitable for general-purpose light field rendering. We include results for different noise types and levels, through murky water and particulate matter, in real-world scenarios, and evaluated using a variety of metrics. We show that the hyperfan's performance scales with aperture count, and demonstrate the inclusion of aliased components for high-quality rendering.
A geometric basis for surface habitat complexity and biodiversity
Publisher: Cold Spring Harbor Laboratory
Date: 04-02-2020
DOI: 10.1101/2020.02.03.929521
Abstract: Structurally complex habitats tend to contain more species and higher total abundances than simple habitats. This ecological paradigm is grounded in first principles: species richness scales with area, and surface area and niche density increase with three-dimensional complexity. Here we present a geometric basis for surface habitats that unifies ecosystems and spatial scales. The theory is framed by fundamental geometric constraints among three structure descriptors—surface height, rugosity and fractal dimension—and explains 98% of surface variation in a structurally complex test system: coral reefs. We then show how coral bio ersity metrics (species richness, total abundance and probability of interspecific encounter) vary over the theoretical structure descriptor plane, demonstrating the value of the theory for predicting the consequences of natural and human modifications of surface structure.
Variable responses of benthic communities to anomalously warm sea temperatures on a high-latitude coral reef
Publisher: Public Library of Science (PLoS)
Date: 26-11-2014
Analysis of propulsion methods for long-range AUVs
Publisher: Marine Technology Society
Date: 03-2010
DOI: 10.4031/MTSJ.44.2.3
Abstract: Abstract Underwater gliders use a buoyancy engine and symmetric wings to produce lift. During operation, gliders follow a saw-tooth trajectory, making them useful vehicles for profiling ocean chemistry. By operating at low speeds with low hotel loads, gliders achieve a high endurance. Man-portable, propeller-driven autonomous underwater vehicles (AUVs) are capable of level flight and can also follow terrain to yield high-quality benthic imagery. These platforms typically operate at high speeds with high hotel loads resulting in relatively low endurance. Although both vehicles are used to collect oceanographic data, constraints on how these vehicles are used differentiate the nature of data they collect. This article examines whether one method of propulsion can provide an intrinsic advantage in terms of horizontal range at low speed, regardless of s ling design. We employ first-principle analysis that concludes that either class of vehicle can be designed to achieve the same horizontal transit performance regardless of speed. This result implies that the choice of propulsion method should be driven exclusively by the application and operational requirements.
True Color Correction of Autonomous Underwater Vehicle Imagery
Publisher: Wiley
Date: 07-10-2016
DOI: 10.1002/ROB.21638
Hierarchical classification in AUV imagery
Publisher: Springer International Publishing
Date: 2015
Towards Adaptive Benthic Habitat Mapping
Publisher: IEEE
Date: 05-2020
Decoding, calibration and rectification for lenselet-based plenoptic cameras
Publisher: IEEE
Date: 06-2013
Seabed modeling and distractor extraction for mobile AUVs using light field filtering
Publisher: IEEE
Date: 05-2011
Dirichlet process mixture models for autonomous habitat classification
Publisher: IEEE
Date: 05-2010
Multi-vehicle localisation with additive compressed factor graphs
Publisher: No publisher found
Date: 2014
AUV-assisted surveying of relic reef sites
Publisher: IEEE
Date: 2008
Discovering salient regions on 3D photo-textured maps: Crowdsourcing interaction data from multitouch smartphones and tablets
Publisher: Elsevier BV
Date: 02-2015
Spectral characterization of COTS RGB cameras using a linear variable edge filter
Publisher: SPIE
Date: 11-01-2013
DOI: 10.1117/12.2001460
Using an autonomous underwater vehicle to inform management of biodiversity in shelf waters.
Publisher: IEEE
Date: 05-2010
Large-scale assessment of benthic communities across multiple marine protected areas using an autonomous underwater vehicle
Publisher: Public Library of Science (PLoS)
Date: 16-03-2018
Mid-water current aided localization for autonomous underwater vehicles
Publisher: Springer Science and Business Media LLC
Date: 11-02-2016
A featureless approach to efficient bathymetric SLAM using distributed particle mapping
Publisher: Wiley
Date: 15-12-2011
DOI: 10.1002/ROB.20382
Australian sea-floor survey data, with images and expert annotations
Publisher: Springer Science and Business Media LLC
Date: 27-10-2015
Abstract: This Australian benthic data set (BENTHOZ-2015) consists of an expert-annotated set of georeferenced benthic images and associated sensor data, captured by an autonomous underwater vehicle (AUV) around Australia. This type of data is of interest to marine scientists studying benthic habitats and organisms. AUVs collect georeferenced images over an area with consistent illumination and altitude, and make it possible to generate broad scale, photo-realistic 3D maps. Marine scientists then typically spend several minutes on each of thousands of images, labeling substratum type and biota at a subset of points. Labels from four Australian research groups were combined using the CATAMI classification scheme, a hierarchical classification scheme based on taxonomy and morphology for scoring marine imagery. This data set consists of 407,968 expert labeled points from around the Australian coast, with associated images, geolocation and other sensor data. The robotic surveys that collected this data form part of Australia's Integrated Marine Observing System (IMOS) ongoing benthic monitoring program. There is reuse potential in marine science, robotics, and computer vision research.
Simple change detection from mobile light field cameras
Publisher: Elsevier BV
Date: 04-2016
Autonomous exploration of large-scale benthic environments
Publisher: IEEE
Date: 05-2013
Feature Space Exploration For Planning Initial Benthic AUV Surveys
Publisher: Field Robotics Publication Society
Date: 10-01-2023
DOI: 10.55417/FR.2023021
Abstract: Special-purpose Autonomous Underwater Vehicles (AUVs) are utilized for benthic (seafloor) surveys, where the vehicle collects optical imagery of the seafloor. Due to the small-sensor footprint of the cameras and the vast areas to be surveyed, these AUVs can not feasibly collect full coverage imagery of areas larger than a few tens of thousands of square meters. Therefore it is necessary for AUV paths to s le the surveys areas sparsely, yet effectively. Broad-scale acoustic bathymetric data are readily available over large areas and are often a useful prior of seafloor cover. As such, prior bathymetry can be used to guide AUV data collection. This research proposes methods for planning initial AUV surveys that efficiently explore a feature space representation of the bathymetry, in order to s le from a erse set of bathymetric terrain. This will enable the AUV to visit areas that likely contain unique habitats and are representative of the entire survey site. We propose several information gathering planners that utilize a feature space exploration reward, to plan freeform paths or to optimize the placement of a survey template. The suitability of these methods to plan AUV surveys is evaluated based on the coverage of the feature space and also the ability to visit all classes of benthic habitat on the initial e. Informative planners based on Rapidly expanding Random Trees (RRT) and Monte Carlo Tree Search (MCTS) were found to be the most effective. This is a valuable tool for AUV surveys as it increases the utility of initial es. It also delivers a comprehensive training set to learn the relationship between acoustic bathymetry and visually derived seafloor classifications.
Model predictive control of an autonomous underwater vehicle in an in situ estimated water current profile
Publisher: IEEE
Date: 05-2012
Implementation of an indoor active sensor network
Publisher: Springer Berlin Heidelberg
Date: 2006
DOI: 10.1007/11552246_38
Editorial: Visual navigation and mapping outdoors
Publisher: Wiley
Date: 03-08-2010
DOI: 10.1002/ROB.20358
Repeated AUV surveying of urchin barrens in north eastern Tasmania
Publisher: IEEE
Date: 05-2010
Corrigendum: Australian sea-floor survey data, with images and expert annotations (Scientific Data (2015) 2 (150057) DOI: 10.1038/sdata.2015.57)
Publisher: Springer Science and Business Media LLC
Date: 20-12-2016
Abstract: Scientific Data 2:150057 doi:10.1038/sdata.2015.57 (2015) Published 27 Oct 2015 Updated 20 Dec 2016 The authors regret that Ezequiel Marzinelli was omitted in error from the author list of the original version of this Data Descriptor. This omission has now been corrected in the HTML and PDF versions of this Data Descriptor.
Autonomous underwater vehicle-assisted surveying of drowned reefs on the shelf edge of the Great Barrier Reef, Australia
Publisher: Wiley
Date: 03-08-2010
DOI: 10.1002/ROB.20356
Outcropping reef ledges drive patterns of epibenthic assemblage diversity on cross-shelf habitats
Publisher: Springer Science and Business Media LLC
Date: 22-02-2016
Learning features from georeferenced seafloor imagery with location guided autoencoders
Publisher: Wiley
Date: 28-05-2021
DOI: 10.1002/ROB.21961
Out-of-core efficient blending for underwater georeferenced textured 3D maps
Publisher: IEEE
Date: 07-2013
Habitat structural complexity metrics improve predictions of fish abundance and distribution
Publisher: Wiley
Date: 04-12-2018
DOI: 10.1111/ECOG.02580
Geomorphic changes of a coral shingle cay measured using Kite Aerial Photography
Publisher: Elsevier BV
Date: 10-2016
Guest editorial
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2012
Surveying noctural cuttlefish camouflage behaviour using an AUV
Publisher: IEEE
Date: 05-2009
Structured output prediction with hierarchical loss functions for seafloor imagery taxonomic categorization
Publisher: Springer International Publishing
Date: 2015
Guiding Labelling Effort for Efficient Learning With Georeferenced Images
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Orca: A component model and repository
Publisher: Springer Berlin Heidelberg
Date: 2007
Topic-based habitat classification using visual data
Publisher: IEEE
Date: 05-2009
Water column current profile aided localisation combined with view-based SLAM for autonomous underwater vehicle navigation
Publisher: IEEE
Date: 05-2011
Synergistic clustering of image and segment descriptors for unsupervised scene understanding
Publisher: IEEE
Date: 12-2013
Simultaneous Localisation and Mapping and Dense Stereoscopic Seafloor Reconstruction Using an AUV
Publisher: Springer Berlin Heidelberg
Date: 2009
Efficient view-based SLAM using visual loop closures
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2008
Quantifying the response of structural complexity and community composition to environmental change in marine communities
Publisher: Wiley
Date: 29-02-2016
DOI: 10.1111/GCB.13197
Abstract: Habitat structural complexity is a key factor shaping marine communities. However, accurate methods for quantifying structural complexity underwater are currently lacking. Loss of structural complexity is linked to ecosystem declines in bio ersity and resilience. We developed new methods using underwater stereo-imagery spanning 4 years (2010-2013) to reconstruct 3D models of coral reef areas and quantified both structural complexity at two spatial resolutions (2.5 and 25 cm) and benthic community composition to characterize changes after an unprecedented thermal anomaly on the west coast of Australia in 2011. Structural complexity increased at both resolutions in quadrats (4 m(2)) that bleached, but not those that did not bleach. Changes in complexity were driven by species-specific responses to warming, highlighting the importance of identifying small-scale dynamics to disentangle ecological responses to disturbance. We demonstrate an effective, repeatable method for quantifying the relationship among community composition, structural complexity and ocean warming, improving predictions of the response of marine ecosystems to environmental change.
Stereo-imaging AUV detects trends in sea urchin abundance on deep overgrazed reefs
Publisher: Wiley
Date: 13-02-2016
DOI: 10.1002/LOM3.10089
Water column current profile aided localisation for autonomous underwater vehicles
Publisher: IEEE
Date: 05-2010
Multimodal learning for autonomous underwater vehicles from visual and bathymetric data
Publisher: IEEE
Date: 05-2014
A geometric basis for surface habitat complexity and biodiversity
Publisher: Springer Science and Business Media LLC
Date: 24-08-2020
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