Intelligent Visual Computing Research Centre
Director: Professor Yonghuai Liu
The Intelligent Visual Computing Research Centre focuses on the topics in the general areas of 3D computer vision, image processing, pattern recognition, visual data analytics, computer graphics, virtual/augmented reality, human sensing and human-robot social interactions. The research is supported by the latest technologies such as the Computer Augmented Virtual Environment (CAVE) and a range of state-of-the-art devices for data acquisition, output, visualisation, and full immersive experiences including: Tobii Eye X, Vive, Z-Space, Kinects, Hype Box, Emotive, Enobio BCI, Nao Robots, 3D Scanner and printer. It has the following goals:
- connecting with stakeholders to impact society
- supporting students to test the latest visual computing techniques and acquire research-lead employability skills
- empowering researchers to solve theoretical and real-world problems in visual computing and utilising virtual and augmented reality technology.
It aims to:
- Visualise the signal, image, shape and video data and their operations with the modern CAVE and other devices.
- enhance the visual data for high contrast and removal of unwanted factors,
- analyse and convert the visual data into semantically meaningful components, models, measurements, relevant knowledge and/or interesting responses and behaviours
- explore data visualisation and AR/VR simulation and applications in the real world such as medical imaging, training, computer aided instruction, CAD, systems automation, additive manufacturing, plant science, robotics, autonomous vehicles, intelligent surveillance, remote sensing, industrial quality assurance, and others.
It currently focuses on, but is not limited to, the following areas:
- 3D shape modelling, analysis and measurements
- camera calibration
- 3D model search and query
- Image noise removal, enhancement and super-resolution.
- Image analysis, decomposition, segmentation, classification and recognition.
- Object detection, classification, recognition and tracking
- Segmentation, clustering, consistency modelling
- Big-data visualisation
- Reflectance modelling, rendering
- Crowd modelling and simulation
- Facial expression and emotion recognition
- Human visual perception
- Human behaviour representation, responses and prediction
- Human activity/pose representation, estimation, classification, and recognition
- CCTV surveillance and management
- Dr Ardhendu Behera
- Professor Yonghuai Liu
- Dr Peter Matthew
- Dr Peter Vangorp,
- Dr Huaizhong Zhang