Dr. Xiaohong W. Gao
Dr. Xiaohong W. Gao
School of Engineering and Information Sciences
Middlesex University
The Burroughs (Town Hall),
Hendon,
London,
NW4 4BT,
United Kingdom
Since 2000 the Laboratory of Neuroinformatics of Sensory and Motor Systems (LNISMS) at A.B. Kogan Research Institute for Neurocybernetics, SFedU is involved in a joint research with Dr. Gao, School of Engineering and Information Sciences, Middlesex University, UK. Collaboration was initiated by British partner and in 2001 during the visit of Natalia Shevtsova, senior researcher of the LNISMS, to the Middlesex University within the frameworks of Exchange Visit Grant ¹ 207043 from the Royal Society, the first series of investigations on the traffic sign recognition problem was fulfilled.
The research in this field is carried out in many (more than 50) research centers and universities (mainly, Western Europe, USA, and Japan). In most cases known works on traffic sign recognition are based on standard computer vision methods, such as correlative, structural and so on. They usually provide a high rate of recognition of traffic signs of some classes (most often, speed limit) and are not sufficiently robust (invariant) to changing traffic sign images with respect to daytime, weather conditions and view. The joint projects "DEVELOPMENT OF BIOLOGICALLY PLAUSIBLE MODELS OF VISION WITH APPLICATION TO REAL WORLD IMAGE ANALYSIS" and "INVARIANT IMAGE RECOGNITION BY IDENTIFICATION OF THEIR MOST INFORMATIVE REGIONS" . are directed to solution of these problems. The main content of the project is a modification of the Behavioral Model of Vision BMV developed earlier in the LNISMS to solve the problem of traffic sign recognition. The BMV demonstrates invariance to various transformations of the visual objects (size, view, plane rotation and noise) and is used as a basic in a number of research centers of Europe, USA (Krasnow Institute, George Mason University), and South Korea (CAVR).
During these collaborative research some new results were obtained which are presented more then 20 joint publications.
Current joint projects:
"REAL-WORLD IMAGES PROCESSING BY DETECTION OF THEIR STABLE REGIONS" , project of science and technology co-operation.
"Head Motion Detection for Positron Emission Tomography (PET) Imaging Scanning", BRIDGE project
Anishchenko S., Osinov V., Shaposhnikov D., Podlachikova L., Comley R., Gao X.W. Toward a Robust System to Monitor Head Motions during PET Based on Facial Landmark Detection: a New Approach. // In proc. 21-st IEEE Int. Symp. On Comp.-Based Med. Sys. - Finland, 2008. šp. 50-52.
Anishenko S., Osinov V., Shaposhnikov D., Podladchikova L., Comley R., Sukholentsev K., Gao X. A Motion Correction System for Brain Tomography Based on Biologically Motivated Models. // In Proc. 7-th IEEE Int. Conf. on Cybernetic Intelligent Sys.. London, UK, 2008. pp. 32-36.
Anishenko S., Shaposhnikov D., Podladchikova L., Comley R., Sukholentsev K., Gao X. W. Head Motion Monitoring Based on Foveal Approach and Local Facial Landmark Detection (Russian version) // In Proc. of 9-th Int. Conf. on Pattern Recognition and Image Analisys: New Information Technologies (PRIA-9-2008). - Nizhni Novgorod, Russia, 2008. v.1. pp. 11-14.
Gao X., Hong K., Podladchikova L., Shaposhnikov D. and Passmore P. Colour Appearance Based Approaches for Segmentation of Traffic Signs. // EURASIP Journal on Image and Video Processing. 2008. - v.2008. - Article ID 386705. - doi:10.1155/2008/386705, - 7 pages.
Gao X.W., Anishenko S., Shaposhnikov D., Podlachikova L., Batty S., and Clark J. High-Precision Detection of Facial Landmarks to Estimate Head Motions Based on Vision Models. // Journal of Computer Science, 3 (7): P. 528-532, 2007.
Gao X.W., Batty S., Podlachikova L., Shaposhnikov D., Clark J. Detection of head motions using a vision model. // In Proc. of 3-d IASTED Int. Conf. TELEHEALTH. - 2007. - P. 167-171.
Gao X.W., Podladchikova L., Shaposhnikov D., Hong K., Shevtsova N. Recognition of traffic signs based on their colour and shape features extracted using human vision models. // J. Visual Communication and Image Representation. - 2006. - 17. - p.675-685.
Gao X., Podladchikova L., Shaposhnikov D. Application of vision models to traffic sign recognition. // Proceedings of the Joint International Conference on Artificial Neural Networks and Neural Information Processing, ICANN/ICONIP, 2003, Turkey, Istanbul, Springer, 2003, 1100-1105.
Shaposhnikov D. G., Podladchikova L. N., and Gao X. Classification of images on the basis of the properties of informative regions. // Pattern Recognition and Image Analysis: Advances in Mathematical Theory and Applications, 2003, V. 13, No 2, 349-352.
Gao X., Shevtsova N., Hong K., Batty S., Podladchikova L., Golovan A., Shaposhnikov D., Gusakova V. Vision models based identification of traffic signs. // Proceeedings of the First European Conference on Color in Graphics, Image and Vision, Poitiers, France, 2-5 April, 2002, 47-51.
Gao X.W., Golovan A.V, Hong K., Podladchikova L.N., Shaposhnikov D.G., Shevtsova N.A. Road sign recognition by means of the behavioral model of vision In Proc. of IV Russian Scientific Conf. "Neuroinformatics-2002", Moscow, Russia, January 22-24, 2002, 63-69.
Shaposhnikov D.G., Podladchikova L.N., Golovan A.V., Shevtsova N.A.,Hong K., Gao X. Road sign recognition by single positioning of space-variant sensor window. // Proceedings of the 15th International Conference on Vision Interface. Canada, Calgary: 2002, 213-217.
Gao X., Shevtsova N., Hong K., Batty S., Podladchikova L., Golovan A., Shaposhnikov D., Gusakova V. A new approach to traffic sign recognition. // Proceedings of the International Conference on Imaging Science, Systems, and Technology, USA, Las-Vegas, 2002, V. 2, 736-741.
Shaposhnikov D.G., Golovan A.V., Podladchikova L.N., Shevtsova N.A., Gao X., Gusakova V I., Gizatdinova Ju. F. Application of the behavioral model of vision to invariant recognition of faces and traffic signs. // Neurocomputers: Design and Application. 2002, No 7-8, 21-33 (in Russian).
Shaposhnikov D.G., Podladchikova L.N., Shevtsova N.A., Golovan A.V., Gao X.W. Invariant recognition of traffic signs. // Proc. of the Anniversary Int. Conf. on Neurocybernetics. - Russia, Rostov-on-Don: 2002, 158-163.
