Dr Xun Li
Casual Academic

Dr Xun Li

• 2010-2013 PhD in Geomatic Engineering at the University of New South Wales -  Vision-based navigation with reality-based 3D maps.

• 2005-2009 Bachelor of Engineering (Honours equivalent) in Software Engineering at Wuhan University, China.


Computer Science and Engineering
My area of research interest is computer vision for real-world applications: intelligent video surveillance, geospatial and agricultural systems.

I obtained my PhD degree from UNSW in late 2013, where I worked on integrating geo-spatial information with computer vision for vision-based mapping and navigation.

In 2014 I joined High Resolution Plant Phenomics Centre (HRPPC), CSIRO and worked in the software team to develop visual processing pipelines/software for agriculture applications. The main goal is to use computer vision technologies, such as machine learning, 3D reconstruction, point cloud processing, and image processing to analyse information collected from various plant phenotyping platforms (including helicopter, UAV, field robotics and controlled environment imaging platforms) and build automated systems for intelligent farming.

In early 2020 I returned to UNSW as a postdoctoral research associate. My current research project is using video analysis to build intelligent surveillance systems, focusing on pedestrian tracking and human action recognition.

  • Journal articles | 2022
    Li X; Onie S; Liang M; Larsen M; Sowmya A, 2022, 'Towards Building a Visual Behaviour Analysis Pipeline for Suicide Detection and Prevention', Sensors, vol. 22, http://dx.doi.org/10.3390/s22124488
    Journal articles | 2013
    Li X; Wang J; Li T, 2013, 'Seamless Positioning and Navigation by Using Geo-Referenced Images and Multi-Sensor Data', SENSORS, vol. 13, pp. 9047 - 9069, http://dx.doi.org/10.3390/s130709047

• 2017-2018 Merit Promotion, CSIRO
• 2010-2013 International Postgraduate Research Scholarship (IPRS)

Dr. Xun Li obtained her PhD degree from UNSW in 2013 on topic vision-based navigation. After graduation, she joined CSIRO to work on Plant Phenotyping and participated in several major projects, and played a key role in the development of the center's imaging platforms. She has currently returned UNSW to work as a research associate at CSE. Her research interests mainly focused on using computer vision for real-world applications:

- Agricultural applications: plant phenotyping via 3D reconstruction of plants, point cloud processing, traditional & machine-learning-based image analysis for RGB, thermal, and fluorescence cameras;

- CCTV: Machine learning (deep learning) for video analysis, such as pedestrian detection, tracking and behavior recognition;

- Geospatial applications: vision-based mapping and positioning;