Grid Seams: A fast superpixel algorithm for real-time applications – VISION AND IMAGE PROCESSING (VIP) RESEARCH GROUP https://vip.uwaterloo.ca The University of Waterloo's Vision and Image Processing Lab Fri, 12 Jan 2024 17:34:02 +0000 en-CA hourly 1 https://wordpress.org/?v=6.7 https://vip.uwaterloo.ca/wp-content/uploads/2023/04/cropped-favicon-32x32.png Grid Seams: A fast superpixel algorithm for real-time applications – VISION AND IMAGE PROCESSING (VIP) RESEARCH GROUP https://vip.uwaterloo.ca 32 32 Linlin Xu https://vip.uwaterloo.ca/linlin-xu/ Wed, 26 Apr 2023 14:17:28 +0000 https://vip.uwaterloo.ca/?p=2523 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

]]> Linlin Xu https://vip.uwaterloo.ca/l-xu/ Wed, 29 Mar 2023 19:13:55 +0000 https://wwwvip.uwaterloo.ca/?p=1372 I am a Research Assistant Professor in the Department of Systems Design Engineering, working on AI, machine learning, Earth Observation and Environmental Remote Sensing projects.

In my key research areas, I have demonstrated excellence, leadership and recognition. I, as principal investigator, have successfully secured many competitive grants, including NSERC Discovery Grant. I have published one book chapter, 66 journal papers on high-rank remote sensing journals and 41 conference articles on high-impact conferences.

I have been involved in many invited talks and presentations to different audiences, and I frequently receive reviewer invitations from high-impact remote sensing journals and conferences. I serve as the Associate Editor of Frontiers in Environmental Science (Section: Big Data, AI and the Environment).

LinkedIn: linkedin.com/linlinxu.

Google Scholar: https://scholar.google.com/linlinxu

Email: l44xu@uwaterloo.ca

Research interests
With the explosion of Earth observation (EO) data, fast EO market growth is bottlenecked by the lack of intelligent analytics that can automatically transfer large-volume, ever-increasing, noisy, heterogeneous raw EO data into compact, real-time, value-added information products. I tailor-design cutting-edge AI solutions to enable automatic generation of scalable EO information products in a high-precision, fast and cost-effective manner to better support various key applications in environmental monitoring, resource exploration and climate change studies. I have strong expertise on AI and machine learning (ML), geospatial data science, different remote sensing techniques (i.e., Hyperspectral, Lidar and SAR remote sensing), and their environmental monitoring applications, e.g., land cover/use classification, hyperspectral mapping of biophysical, biochemical, and geochemical parameters, oil spill detection, and high-resolution Pan-Arctic sea/lake ice mapping.

Students

Supervision – Current

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Ph.D

Javier Noa Turnes

M.A.Sc

Niloofar Azad, Jayden Hsiao

Supervision – Completed

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Yuan Fang (2023)

Ph.D

Saeid Taleghanidoozdoozan (2023), Yuan Fang (2022), Mohsen Ghanbari (2021)

M.A.Sc

Mohammad Basri (2024), Muhammed Patel (2024), Yifan Wu (2022), Peter Q. Lee (2020)

Research topics
Computer Vision
Image Segmentation/Classification
Remote Sensing
Stochastic Models
Research demos
Compressed Sensing
Disparate Scene Registration
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

]]> Parthipan Siva https://vip.uwaterloo.ca/p-siva/ Thu, 23 Mar 2023 16:33:49 +0000 https://wwwvip.uwaterloo.ca/?p=1069 Parthipan Siva received a B.A.Sc. in Systems Design Engineering from the University of Waterloo, Canada, in 2005 and a M.A.Sc. in Systems Design Engineering from the University of Waterloo, Canada, in 2007. He has worked in industry developing real-time video analytics software for surveillance applications. He is currently pursuing his Ph.D. in Computer Science at Queen Mary University of London. His research interests include video analytics and pattern recognition with focus on activity detection and monitoring for surveillance applications.

Email: psiva@eecs.qmul.ac.uk

Personal Website: http://www.psiva.ca

Supervisors
David Clausi
Research interests
My research interests are primarily in the field of computer vision and pattern recognition with a focus on video analytics. I am particularly interested in action/activity recognition in videos using a weakly supervised approach.
Research topics
Computer Vision
Evolutionary Deep Intelligence
Video Analysis
Research demos
Grid Seams: A fast superpixel algorithm for real-time applications
Publications
Journal Articles

Conference Papers

]]> Grid Seams: A fast superpixel algorithm for real-time applications https://vip.uwaterloo.ca/grid-seams-a-fast-superpixel-algorithm-for-real-time-applications/ Tue, 21 Mar 2023 16:01:49 +0000 https://wwwvip.uwaterloo.ca/?p=943
Overall architecture of the Grid Seams approach

Grid Seams is a novel seam carving approach to superpixel generation that preserves image structure information while enforcing a global spatial constraint in the form of a grid structure cost. The seam based approach allows us to obtain superpixels faster than all existing methods while maintaining a high image representation accuracy. Furthermore, our approach allows us to easily incorporate not only structural information but other useful image properties such as texture.

Files

GridSeam.zip.zip

Related people

Directors

Alexander Wong

Students

Alumni

Linlin Xu, Parthipan Siva

Related research areas

Computer Vision

Image Segmentation/Classification

]]> Alexander Wong https://vip.uwaterloo.ca/a-wong/ Thu, 23 Feb 2023 21:38:59 +0000 https://wwwvip.uwaterloo.ca/?p=491 Alexander Wong is currently the Canada Research Chair in Medical Imaging Systems and an assistant professor in the Department of Systems Design Engineering at the University of Waterloo. He had previously received his B.A.Sc. degree in Computer Engineering from the University of Waterloo, Waterloo, ON, Canada in 2005, his M.A.Sc. degree in Electrical and Computer Engineering from the University of Waterloo, Waterloo, ON, Canada in 2007, and his Ph.D. degree Systems Design Engineering from the University of Waterloo, ON, Canada in 2010. He was also a NSERC postdoctoral research fellow at Sunnybrook Health Sciences Centre.  He has published over 450 refereed journal and conference papers, as well as patents, in various fields such as computational imaging, artificial intelligence, computer vision, and multimedia systems. He has received numerous awards including three Outstanding Performance Awards, a Distinguished Performance Award, an Engineering Research Excellence Award, a Sandford Fleming Teaching Excellence Award, an Early Researcher Award from the Ministry of Economic Development and Innovation, a Best Paper Award at the NIPS Workshop on NIPS Workshop on Transparent and Interpretable Machine Learning (2017), a Best Paper Award at the NIPS Workshop on Efficient Methods for Deep Neural Networks (2016), two Best Paper Awards by the Canadian Image Processing and Pattern Recognition Society (CIPPRS) (2009 and 2014), a Distinguished Paper Award by the Society of Information Display (2015), two Best Paper Awards for the Conference of Computer Vision and Imaging Systems (CVIS) (2015,2017), Synaptive Best Medical Imaging Paper Award (2016), two Magna Cum Laude Awards and one Cum Laude Award from the Annual Meeting of the Imaging Network of Ontario, CIX TOP 20 (2017), AquaHacking Challenge First Prize (2017), Best Student Paper at Ottawa Hockey Analytics Conference (2017), and the Alumni Gold Medal.

Students

Supervision – Current

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ph.D.

Ziyao Shang, Amy Tai

M.A.Sc.

Supervision – Completed

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Yuhao Chen (2023), Mehrnaz Fani (2019-2022), Linlin Xu (2016), Hicham Sekkati (2016), Christian Scharfenberger (2014)

ph.D.

Mingzhe (Major) Jiang (2022), Zilong Zhong (2021), Audrey Chung (2020), Robert Amelard (2017), Shahid Haider (), Farnoud Kazemzadeh (2016), Daniel S. Cho (2016), Fan Li (2015), Shimon Schwartz (2013), Chenyi Liu (2012)

M.A.Sc.

Chang Liu (2025), Vasyl Chomko (2025), Saeejith Nair (), Kimathi Kaai (2024), Brennan Gebotys (2022), Chi-en (Amy) Tai (), Marjan Shahi (), Pascale Walters (2021), Chris Dulhanty (2020), Ahmadreza Jeddi (2020), Edward Li (2016), Francis Li (2016), Brendan Chwyl (2016), Shahid Haider (2015), Andrew Cameron (2014), Dorothy Lui (2014), Robert Amelard (2013), Hayden Gunraj (), Jeffrey Glaister (2013), Aanchal Jain (2012)

Research topics
Biomedical Imaging
Computer Vision
Discovery Radiomics
Evolutionary Deep Intelligence
Image Segmentation/Classification
Multiresolution Techniques
Remote Sensing
Scientific Imaging
Stochastic Models
Video Analysis
Research demos
Action Recognition in Video
Bias Field Correction in Endorectal Diffusion Imaging
Coded Hemodynamic Imaging
Correlated Diffusion Imaging
Disparate Scene Registration
Enhanced Decoupled Active Contour Using Structural and Textural Variation Energy Functionals
Enhanced Low-dose Computed Tomography
Grid Seams: A fast superpixel algorithm for real-time applications
Hybrid Structural and Texture Distinctiveness Vector Field Convolution for Region Segmentation
Image Denoising
Multiplexed Optical High-coherence Interferometry
SAR Sea Ice Image Synthesis
Skin Cancer Detection
Statistical Textural Distinctiveness for Salient Region Detection in Natural Images
Stereo Vision for Dimension Estimation
Publications
Journal Articles

Conference Papers

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