MVA Most Influential Paper over the Decade Award is given to the authors of a paper which was presented ten years ago at the IAPR Conference on Machine Vision Applications (MVA), and has been recognised as having had the most significant influence on machine vision technology over the subsequent decade.
The awarded paper, A New Approach for In-Vehicle Camera Traffic Sign Detection and Recognition, presents a method for real-time detection, tracking and recognition of traffic signs from in-vehicle camera was developed in this work. It effectively addressed several key issues for the underlying problem: fast estimation of regions of interest by taking advantage of the particular characteristics of traffic signs (e.g. limited number of contrasting colours), view-invariant detection/tracking using Lie algebra, and recognition using pair-wise similarity and AdaBoost.
Dr. Yongmin Li works in the areas of computer vision, image processing, video analysis, medical imaging, bio-imaging, machine learning, pattern recognition, automatic control and nonlinear filtering. Before joining Brunel University, he worked as a research scientist in the British Telecom Laboratories. Dr. Li is a Senior Member of the IEEE, and Fellow of the Higher Education Academy.