Improved motion segmentation based on shadow detection

In this paper, we discuss common colour models for background subtraction and problems related to their utilisation are discussed. A novel approach to represent chrominance information more suitable for robust background modelling and shadow suppression is proposed. Our method relies on the ability to represent colours in terms of a 3D-polar coordinate system having saturation independent of the brightness function; specifically, we build upon an Improved Hue, Luminance, and Saturation space (IHLS). The additional peculiarity of the approach is that we deal with the problem of unstable hue values at low saturation by modelling the hue-saturation relationship using saturation-weighted hue statistics. The effectiveness of the proposed method is shown in an experimental comparison with approaches based on RGB, Normalised RGB and HSV

Mobile Robot Localization under Varying Illumination

Methods for mobile robot localization that use eigenspaces of panoramic snapshots of the environment are in general sensitive to changes in the illumination of the environment. Therefore, we propose in this paper an approach which achieves a reliable localization under severe illumination conditions by illumination insensitive eigenspaces. The method in question uses gradient filtering of the eigenspaces. The method was tested on images obtained by a mobile robot and, as we show, it outperforms by far the other known methods

regions

texture representation using multi-scal