Minglun Gong

Professor; Director, School of Computer Science

College of Computational, Mathematical and Physical Sciences, School of Computer Science

Seeking academic or industry partnerships in the area(s) of

Apply Computer Vision and Artificial Intelligence techniques to smart sensing, including but not limiting to, object tracking and crowd density estimation. Apply Computer Graphics techniques for 3D reconstructions of large-scale urban scenes.

Available positions for grads/undergrads/postdoctoral fellows

Yes

Research Areas

Graphics
Computer Vision

Instrumentation

DJI Matrice 210 V2 and DJI Matrice 600 Pro
DJI Zenmuse XT2 and DJI Zenmuse Z30

Capabilities

Take aerial photos and capture both visible light and thermal images.

Education and Employment Background

Dr. Minglun Gong received his PhD in Computer Science from the University of Alberta in 2003 and joined Laurentian University as an Assistant Professor after graduation. In 2007, Gong moved to Memorial University of Newfoundland, where he was promoted to Associate Professor in 2010 and Full Professor in 2015. Gong has held several Visiting Professor positions at the Shenzhen Institute of Advanced technology and the Shenzhen University in China. In 2019, Gong joined the School of Computer Sciences at the University of Guelph, where he is currently a Full Professor and Director of the school.

Research Themes

Gong’s research interests span a variety of topics in visual computing. He conducts research on computer graphics, computer vision, visualization, image processing, and artificial intelligence. Key research themes include:

Geometric modeling and geometry processing. Gong and his research team use computers to capture the geometric details of an object for reconstruction. He has applied his research on plants, mobile robots, flowers, and deformable objects. Gong and his team have explored new methods and approaches for refining geometric modeling and geometry processing.
Image and video synthesis. Gong uses AI and algorithms to train image translators, develop face photo stylization, and solve challenges in image and video translation.
Image processing. Gong explores challenges related to image processing including hierarchical colour image segmentation and distilled collections from textual image queries.
Refractive imaging. With novel approaches to physical refraction models, Gong explores 3D reconstruction techniques related to transparent objects and underwater imagery.
Foreground segmentation and matting. Again, applying computer algorithms, Gong explores video with natural backgrounds, fuzzy object boundaries, camera motion, and low colour contrast. He explores the challenge associated with foreground separation from the background modeling perspective.
Stereo vision. Real-time stereo estimation has several important applications in robotics and image-based modeling and rendering. Gong has explored how to perform stereo matching on Graphics Processing Units of modern programmable graphics cards. He has developed a new stereo matching algorithm that considers surface orientation at the per-pixel level. He has also developed a new reliability measure for evaluating stereo matches.
Motion estimation. Gong and his team are also interested in detecting and estimating motions of fast-moving objects. He has used reliability-based dynamic programming (DP) to solve large motion estimation problems.
Information visualization. Gong also explores ways in which information can be visualized. For example, how to position data into a structured layout so that proximity reflects similarity, performing automatic query expansion for users searching for images online, and ways to facilitate users to locate desired photos amongst a collection.
Rendering. Rendering is the process of creating an image from a 2D or 3D model. Gong explores ways in which to reconstruct scenes with new approaches to image-based rendering.
Evolutionary computation. Gong also applies novel algorithms to the study of biological evolution. He has explored applications for bee colonies as well as genetic algorithms.

Highlights

Natural Sciences and Engineering Research Council of Canada (NSERC), Research Tools and Instruments, 2003-2004, 2016–2017, 2018–2019
NSERC Discovery Grant, 2003-2007, 2007–2012, 2012-2017, 2017–2023
Associate editor for Pattern Recognition, 2014–present
Associate editor for IEEE Signal Processing Letters, 2020- present
New Opportunity Fund Award, Canada Foundation for Innovation, 2005
Izaak Walton Killam Memorial Scholarship. 2002–2003

Media Coverage

COVID-19 Research

CEPS News: Preventing and Understanding COVID-19

Grants and Awards

Memorial University Gazette: From Robots to Algae: NSERC funding empowers Memorial researchers to better the world