Support Vector Machines (SVMs) are both mathematically well-funded and efficient in a large number of realworld applications. However, the classification results highly depend on the parameters of the model: the scale of the kernel and the regularization parameter. Estimating these parameters is referred to as tuning. Tuning requires to estimate the generalization error and to find its minimum over the parameter space. Classical methods use a local minimization approach. After empirically showing that the tuning of parameters presents local minima, we investigate in this paper the use of global minimization techniques, namely genetic algorithms and simulated annealing. This latter approach is compared to the standard tuning frameworks and provides a more reliable tuning method.

No abstract

No abstract

No abstract

Video-frame-rate millimetre-wave imaging has recently been demonstrated with a quality similar to that of a low-quality uncooled thermal imager. In this paper we will discuss initial investigations into the transfer of image processing algorithms from more mature imaging modalities to millimetre-wave imagery.The current aim is to develop body segmentation algorithms for use in object detection and analysis. However, this requires a variety of image processing algorithms from different domains, including image de-noising, segmentation and motion tracking. This paper focuses on results from the segmentation of a body from the millimetre-wave images and a qualitative comparison of different approaches is presented. Their performance is analysed and any characteristics which enhance or limit their application are discussed.While it is possible to apply image processing algorithms developed for the visible-band directly to millimetrewave images, the physics of the image formation process is very different. This paper discusses the potential for exploiting an understanding of the physics of image formation in the image segmentation process to enhance classification of scene components and, thereby, improve segmentation performance. This paper presents some results from a millimetre-wave image formation simulator, including synthetic images with multiple objects in the scene.