Visual Information Processing
As humans we perform remarkably well in utilising our sense of vision in such tasks as navigating in complex environments, categorising objects - even objects we have not seen before, interacting with dynamically evolving surroundings or indeed predicting complex behaviours. We can do all of this, apparently with ease, in an instant. Of course, as humans we take these faculties for granted, but it has proved extremely challenging to reproduce these on machines.
With continued advances in mathematical modelling, ever increasing computational power and the recent unprecedented proliferation of shared information (e.g. with reported hundreds of hours of video uploaded to the YouTube servers every minute) or creation of large databases, most notably in bioimaging, machine learning has had in the recent years a profound impact on visual information processing with many of the difficult vision problems successfully solved using the machine learning approaches.
The talk will introduce the field of computer vision, including a small number of practical implementation examples to succinctly illustrate the key computer vision and machine learning concepts.
Date and Time
- Date: 17 Dec 2019
- Time: 01:15 PM to 03:00 PM
- All times are (UTC+01:00) Warsaw
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- Co-sponsored by Wroclaw University of Science and Technology
Professor Matuszewski has been with the University of Central Lancashire since 1997. He heads the Computer Vision and Machine Learning (CVML) Research Group. He is also the deputy director of the UCLan Research Centre in Engineering. He is a member of the Institute of Electrical and Electronics Engineers (IEEE), the British Machine Vision Association (BMVA) and the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society. He has published over 140 research papers in different areas of computer vision and medical image processing and successfully supervised to completion 15 PhDs. He has active collaborative links with industry, number of hospitals and universities across Europe. He has participated in 21 research projects, leading 11 of them. Professor Matuszewski main research interest is in analysis of visual information working in the areas of medical and industrial computer vision and machine learning. He is particularly interested in use of Bayesian methodology for data modelling, pattern recognition and tracking; statistical shape analysis; deformation modelling for model-based recognition, segmentation and registration and applications of deep learning.