Floating search methods in feature selection
Pattern Recognition Letters
The nature of statistical learning theory
The nature of statistical learning theory
A decision-theoretic generalization of on-line learning and an application to boosting
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
Model Complexity Validation for PDF Estimation Using Gaussian Mixtures
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Guest Editorial Introduction To The Special Issue On Automatic Target Detection And Recognition
IEEE Transactions on Image Processing
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This paper is concerned with the detection of dim targets in cluttered image sequences. It is an extension of our previous work [7] in which we viewed target detection as an outlier detection problem. In that work the background was modelled by a uni-modal Gaussian. In this paper a Gaussian mixture-model is used to describe the background in which the the number of components is automatically selected. As an outlier does not automatically imply a target, a final stage has been added in which all points below a set density function value are passed to a support vector classifier to be identified as a target or background. This system is compared favourably to a baseline technique [12].