Visual Computing research covers a range of topics including vision, graphics, intelligent behaviour understanding, and biomedical image computing. The work of the section has led to more than 8 best paper awards at major international conferences (IEEE FG, ICRA, ISMAR, MICCAI, SensorComm) and attracted four Marie Curie fellows.
The group has pursued a successful strategy of growth in several key areas novel modelling and filtering approaches for SLAM and real-time dense scene mapping. Intelligent behaviour understanding, novel approaches to facial action and emotion prediction as well as novel approaches to robust face alignment, tracking and expression recognition, biomedical imaging computing, robotics & sensing, and appearance modelling for realistic computer graphics.
Related videos
Getting robots in the future to truly see
Discussing the advances in developing robotic vision
Professor Andrew Davison and Dr Stefan Leutenegger from the Dyson Robotics Lab at Imperial College London discuss the advances they are making in developing robotic vision.
Deep Learning in Medical Imaging - Ben Glocker #reworkDL
Machines capable of analysing and interpreting medical scans with super-human performance
Machines capable of analysing and interpreting medical scans with super-human performance are within reach. Deep learning, in particular, has emerged as a promising tool in our work on automatically detecting brain damage. But getting from the lab into clinical practice comes with great challenges.
Andy Davison - Robots with vision
Unveiling plans to help robots understand more about the world around them
Current domestic robots are pretty dumb, unable to perform many chores promised by ‘Home of the future’ style TV shows of the 60s. With poor spatial awareness a key limiting factor, Professor Andrew Davison unveils plans to help robots understand more about the world around them.
Robot art
Computer software that enables the user to control a robotic arm with eye commands
Engineers from Imperial College London have developed computer software that enables the user to control a robotic arm with eye commands to paint a simple picture.
Research groups and centres
Academics
Academics
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Dr Tolga Birdal
Location
Huxley Building
Research interests
3D computer vision, geometric machine learning, non-euclidean geometry, topological deep learning .
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Dr Wenjia Bai
Location
Data Science Institute, William Penney Laboratory
Research interests
Medical image analysis and understanding, machine learning.
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Prof. Andrew Davison
Location
303, William Penney Laboratory
Research interests
Computer vision, robotics, Simultaneous Localisation and Mapping (SLAM), augmented reality.
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Prof Aldo Faisal
Location
407A, Huxley Building
4.08, Royal School of MinesResearch interests
Neurotechnology, biomedical engineering, machine learning, algorithmic prediction of human behaviour.
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Dr Abhijeet Ghosh
Location
376, Huxley Building
Research interests
Appearance modeling, computational illumination, photography for graphics and vision.
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Prof Ben Glocker
Personal details
Prof Ben Glocker Professor in Medical Image ComputingSend email+44 (0)20 7594 8334
Location
377, Huxley Building
Research interests
Biomedical image analysis, computer vision, semantic image understanding, machine learning.
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Dr Edward Johns
Location
365, ACEX Building
Research Interest
Robot Learning , Robot Manipulation, Deep Learning, Reinforcement Learning, Computer Vision
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Dr Bernhard Kainz
Location
372, Huxley Building
Research interests
Machine learning, visualisation, interactive real-time image processing, high-performance medical data analysis.
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Prof. Maja Pantic
Personal details
Prof. Maja Pantic Professor of Affective & Behavioural ComputingSend email+44 (0)20 7594 8195
Location
380, Huxley Building
Research interests
Computer vision, machine learning, and affective computing.
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Islem Rekik
Location
5th floor, Imperial-X (I-HUB) White City Campus
Research interests
Machine learning, deep learning, predictive intelligence in medicine, network neuroscience, holistic artificial intelligence.
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Prof. Daniel Rueckert
Personal details
Prof. Daniel Rueckert Professor of Visual Information ProcessingSend email+44 (0)20 7594 8333
Location
568, Huxley Building
Research interests
Image acquisition and analysis using machine learning, medical applications.
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Dr Viktoriia Sharmanska
Location
452, Huxley Building
Research interests
Computer Vision, Machine Learning, Deep Learning methods, Crowdsourcing.
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Prof Bjoern Schuller
Location
574, Huxley Building
Research interests
Machine Learning, Audio-visual signal processing, human-computer/robot-interaction, and affective computing.
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Prof. Guang-Zhong Yang
Location
B411-412, Bessemer Building
Research interests
Professor Yang’s main research interests are in medical imaging, sensing and robotics. In imaging, he is credited for a number of novel MR phase contrast velocity imaging and computational modelling techniques that have transformed in vivo blood flow quantification and visualization.
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Dr Stefanos Zafeiriou
Location
375, Huxley Building
Research interests
Machine learning, computer vision, and image/signal analysis.