Biometric identification using gait

We explored surveillance solutions based on gait recognition, i.e., the identification of people based on their walking style. Compared to other biometrics, gait has some unique characteristics. The most attractive feature of gait as a biometric trait is its unobtrusiveness, i.e., the fact that, unlike other biometrics, it can be captured at a distance. Although the study of kinesiological parameters that define human gait can form a basis for identification, there are apparent limitations in gait capturing that make it extremely difficult to identify and record all parameters that affect gait. In practice, gait recognition systems have to rely on a video sequence that is taken in uncontrolled environments.

When capturing conditions cannot be controlled, a variety of problems arise due to occlusions, varying illumination levels, cluttered backgrounds, or changing walking directions. We developed methodologies that dealt with these problems and delivered superior recognition performance, exceeding 95%, without relying on texture or facial information.

Our systems relied both on model-based approaches, where a human model was the basis for gait modelling, and holistic techniques, where the shape of human silhouettes was the only information used.

Meet the Principal Investigator(s) for the project

Dr Nikolaos Boulgouris - Nikolaos V. Boulgouris is a Reader (Associate Professor) with the Department of Electronic and Electrical Engineering of Brunel University of London. From 2004 to 2010 he was an academic member of staff with King's College London, and before that he was a researcher with the Department of Electrical and Computer Engineering of the University of Toronto, Canada. He has published more than 100 papers in international journals and conferences (Google scholar search) and he has participated in numerous national and international research consortia. Dr. Boulgouris served as Senior Area Editor for the IEEE Transactions on Image Processing. In 2018 he served as Technical Program Chair for the IEEE International Conference on Image Processing (ICIP). In the past he served as Associate Editor for the IEEE Transactions on Circuits and Systems for Video Technology, from which he received the 2017 Best Associate Editor Award, and also as Associate Editor for the IEEE Transactions on Image Processing, and the IEEE Signal Processing Letters. He was co-editor of the book Biometrics: Theory, Methods, and Applications, which was published by Wiley - IEEE Press, and guest co-editor for two journal special issues. He served an elected member of the IEEE Multimedia Signal Processing Technical Committee (MMSP - TC). From 2014 to 2019, he served as an elected member of the IEEE Image, Video, and Multidimensional Signal Processing Technical Committee (IVMSP - TC). Dr. Boulgouris is a Senior Member of the IEEE and a Fellow of the Higher Education Academy.  Please go to https://people.brunel.ac.uk/~eestnnb/ for more details.

Related Research Group(s)

Biomedical Engineering - Research in the growing multi-disciplinary field of advanced technology as devices, processes and modelling to advance health through improvements in therapy, diagnosis, screening, monitoring and rehabilitation.

Project last modified 29/06/2021