Mingqi Gao

Mingqi Gao (高明琦)

PhD candidate in Computer Vision

Biography

Hi! I am Mingqi, a third-year (2021-2022) joint PhD candidate at University of Warwick and Southern University of Science and Technology (SUSTech). Currently, I am doing research in the WMG Data Science Group and SUSTech VIP Lab, under the supervision of Prof. Jungong Han, Prof. Feng Zheng, and Prof. Giovanni Montana. Prior to this, I received my Master degree and Bachelor degree from Chongqing University and Inner Mongolia University respectively.

My research lies in Computer Vision, Pattern Recognition and Deep Learning. Recently, I am dedicating on developing new algorithms for video object segmentation.

News

[17-Jan-2019] - 1 paper is accepted by Signal Processing.

SELECTED PUBLICATIONS

Please see my full publication list from HERE or my Google Scholar Profile

Mingqi Gao, Hengxin Chen, Shenhai Zheng, and Bin Fang. ''Feature fusion and non-negative matrix factorization based active contours for texture segmentation''. Signal Processing, 2019. [link]
Hengxin Chen, Mingqi Gao, Weiliang Xu, Karl Ricanek, and Bin Fang. ''A novel race classification method based on periocular features fusion''. International Journal of Pattern Recognition and Artificial Intelligents (IJPRAI), 2017. [link]
Hengxin Chen, Mingqi Gao, and Bin Fang. ''An improved active shape model method for facial landmarking based on relative position feature''. International Journal of Wavelets, Multiresolution and Information Processing (IJWMIP), 2017. [link]
Mingqi Gao, Hengxin Chen, Shenhai Zheng, Bin Fang, and Lin Zhang. ''Texture image segmentation using fused features and active contour''. IEEE International Conference on Pattern Recognition (ICPR), 2016. [link]
Mingqi Gao, Hengxin Chen, Shenhai Zheng, and Bin Fang. ''A factorization based active contour model for texture segmentation''. IEEE International Conference on Image Processing (ICIP), 2016. [link], [project page], [code]

RESEARCH

My research lies in computer vision, pattern recognition and deep learning. I have been working on the following research topics:

Active Contour / Level Set based Image Segmentation

An iterative method for image segmentation where region boundary is achieved by evolving a closed and smooth contour (red curve).

Typical ACMs and codes

My research work (FACM)

Deep Learning based Video Object Segmentation

Under construction.

MISCELLANEOUS

Honors and Awards

National Scholarship for Graduate Students (top 2%), Ministry of Education, China, 2016.
The 2nd Prize, in China Graduate Contest on Application, Design and Innovation of Mobile-Terminal (top 10%), Beijing, China, 2015.
The 3rd Prize, in National Post-Graduate Mathematic Contest in Modeling, Beijing, China, 2015.

Journal Reviews

Journal of Visual Communication and Image Representation, Pattern Recognition Letters, IET Image Processing