3D Reconstruction of Underwater Scenes – VISION AND IMAGE PROCESSING (VIP) RESEARCH GROUP

Linlin Xu

Linlin Xu — Wed, 26 Apr 2023 14:17:28 +0000

I am a post-doc in Vision and Image Processing Lab, working with professors David Clausi, Alexander Wong, Fan Li, and Steven Leigh, on machine learning, intelligent remote sensing analytics and environmental monitoring.

I recieved my PhD degree in Geography in 2014 from Department of Geography and Environment Management, University of Waterloo. I achieved my Master in 2010 and Bachelor degrees in 2007, both in geomatics engineering, from China University of Geosciences (Beijing).

Research interests

My research interests lie broadly in the following aspects: (1) SAR, PolSAR data processing and the associated applications, particularly in ocean environment monitoring; (2) Hyperspectral and multispectral unmixing, classification, segmentation, feature extraction, and the associated applications; (3) Quantitative and computational methods in remote sensing and other geospatial application, spatial-multivariate data modeling and mining, quantitative remote sensing, image processing & computer vision, GIS, WebGIS; (4) GPS and InSAR data processing with the application in subside monitoring and DEM production; (5) Airborne, mobile, and terrestrial laser scanning mapping for land observation and 3D object modelling.

Research topics

Research demos

3D Reconstruction of Underwater Scenes
Grid Seams: A fast superpixel algorithm for real-time applications
MAGIC System
SAR Sea Ice Image Synthesis
Satellite SAR Sea Ice Classification
Texture Classification

Publications

Journal Articles / Conference Papers

Journal Articles

Conference Papers

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Neil Cavan

vipadmin — Thu, 23 Mar 2023 20:21:25 +0000

Neil Cavan completed his undergraduate degree in Mechanical Engineering at the University of Waterloo in 2007. After working as a mechanical designer for two years, he completed his MASc in Systems Design engineering in August 2011 and is currently employed at 2G Robotics.

Supervisors

David Clausi, Paul Fieguth

Research interests

My research interests include robotics and computer vision, specifically 3D reconstruction of unknown scenes and simultaneous localization and mapping (SLAM) for robotic vehicles.

Research topics

Computer Vision
Video Analysis

Research demos

3D Reconstruction of Underwater Scenes

Publications

Journal Articles / Conference Papers

Journal Articles

Conference Papers

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3D Reconstruction of Underwater Scenes

vipadmin — Thu, 16 Mar 2023 16:10:22 +0000

There is a large and growing demand across many industries for underwater inspection technologies. Whether the assets in question are offshore oil rigs owned by energy companies, undersea power or data cables owned by utilities, or large pipe networks owned by municipalities, the problem is the same: critical assets are in need of assessment and maintenance but inspection is difficult and expensive due to their underwater location. Currently, much of the work in the industry consists of flying a remotely operated underwater vehicle equipped with a camera to take video of these assets in order to determine their state and whether maintenance is required. These videos can be many hours in length, and must be reviewed by a specialist at significant cost to assess the state of the asset.

This research project was undertaken in participation with 2G Robotics Inc., a company focused on underwater inspection. The goal is to implement computer software that can convert pre-existing single-camera videos of an asset, with unknown or varying camera parameters (auto-focus or zooming is allowed), to a photo-realistic 3D model of the asset. With such a model, the client can rotate, zoom, and generally inspect the asset much more quickly and intuitively without the need to review hours of video. There is demand for such software, and the resulting library could be licensed to inspection companies or offered under the Software-as-Service model.

Videos are reconstructed in three stages:

1) Video Tracking – image features are detected in the video, and tracked using optical flow. This produces a set of image correspondences, representing distinct 3D points imaged from many different locations.

2) Projective Reconstruction – using three-view geometry, the 3D structure of the scene and the motion of the video camera are solved simultaneously. The algorithm is robust to noise and mislabeled data.

3) Autocalibration – A projective reconstruction is not suitable for visualization or measurement – in projective geometry, concepts of distance and parallelism have no meaning. In order to transform the projective reconstruction into a metric space, the camera properties must be estimated. This research project has developed a hybrid autocalibration method that combines the best aspects of two existing algorithms. By making basic assumptions about the physical properties of the cameras, the hybrid method can produce a metric 3D reconstruction. In its current state, the 3D reconstruction algorithm can produce point cloud data from underwater video sequences. Future work will allow the point cloud to be meshed and textured with image data, producing a photorealistic 3D model.

Related people

Directors

Students

Alumni

Downloads

shipbow-trackedfeatures.zip

shipbow-3dreconstruction.zip

Related publications

Theses

Cavan, N., “Reconstruction of 3D Points From Uncalibrated Underwater Video“, Systems Design Engineering, Waterloo, ON, University of Waterloo, 2011.

Paul Fieguth

Paul Fieguth — Thu, 23 Feb 2023 20:12:37 +0000

Paul Fieguth received his B.A.Sc. degree from the University of Waterloo, Ontario, Canada, in 1991 and his Ph.D. degree from the Massachusetts Institute of Technology, Cambridge, in 1995, both degrees in electrical engineering. He joined the faculty at the University of Waterloo in 1996, where he is currently Professor and, since 2010, Department Chair in Systems Design Engineering. He has held visiting appointments at the University of Heidelberg in Germany, at INRIA/Sophia in France, at the Cambridge Research Laboratory in Boston, at Oxford University and the Rutherford Appleton Laboratory in England, and with postdoctoral positions in Computer Science at the University of Toronto and in Information and Decision Systems at MIT.

Students

Supervision – Current

PDF

ph.D.

M.A.Sc.

Supervision – Completed

PDF

ph.D.

M.A.Sc.

Research topics

Biomedical Imaging
BIOSCAN Insect Biodiversity Assessment
Computer Vision
Image Segmentation/Classification
Multiresolution Techniques
Remote Sensing
Scientific Imaging
Stochastic Models
Video Analysis

Research demos

3D Reconstruction of Underwater Scenes
Decoupled Active Contours
Image Denoising
Porous Media
SAR Sea Ice Image Synthesis
Skin Cancer Detection
Texture Classification

Publications

Journal Articles / Conference Papers

Journal Articles

Conference Papers

Top

David Clausi

David A Clausi — Mon, 13 Feb 2023 20:18:05 +0000

I completed my Ph.D. in Systems Design Engineering in 1996 and immediately afterwards, I worked in software medical imaging field at Agfa (nee Mitra) in Waterloo, Ontario. I started my academic career in 1997 as an Assistant Professor in Geomatics Engineering at the University of Calgary, Canada. In 1999, I returned to my alma mater and I am now a Professor specializing in the fields of Intelligent and Environmental Systems. In addition, I was the Associate Chair – Graduate Studies (2009-2012). I was the Co-chair of IAPR Technical Committee 7 – Remote Sensing during 2004-2006. I have numerous recognitions, including received five Outstanding Performance Awards, three Distinguished Performance Awards, the Sanford Fleming Teaching Excellence Award, and a University of Calgary Teaching Excellence Award. In 2010, I received the award for “Research Excellence and Service to the Research Community” by the Canadian Image Processing and Pattern Recognition Society (CIPPRS). In 2012, I received the Engineering Research Excellence Award.

Currently, I am the Associate Dean – Research & External Partnerships within the Faculty of Engineering, responsible for all research related activities in the largest Engineering school in Canada.

Research interests

My research interests are in the fields of computer vision, image processing, and pattern recognition with an emphasis on the automated interpretation of SAR (synthetic aperture radar) and sports analytics (ice hockey). I am an active interdisciplinary and multidisciplinary researcher, publishing refereed journal and conference papers in the diverse fields of remote sensing, sports analytics, computer vision, algorithm design, and biomechanics. My research efforts have led to successful commercial implementations including creating and selling a startup company (CREZ).