Tracking and data association
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Efficient k-Means Clustering Algorithm: Analysis and Implementation
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
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In this paper, we present a system for the automatic detection and tracking of metallic objects concealed on moving people in sequences of millimetre-wave images, which can penetrate clothing, plastics and fabrics. The subjects are required to enter one at a time and turn round slowly to ensure complete coverage for the scan. The system employs two distinct stages: detection and tracking. In this paper a single detector, for metallic objects, is presented which utilises a statistical model also developed in this paper. Target tracking is performed using a particle filter. Results are presented on real millimetre-wave image test sequences and indicate an excellent rate of success for threat identification. Encouraging results for target tracking are also reported.