Face tracking using the Dynamic Grey World Algorithm

In this paper we present a colour constancy algorithm for real-time face tracking. It is based on a modification of the well known Grey World algorithm in order to use the redundant information available in an image sequence. In the experiments conducted it is clearly more robust to sudden illuminant colour changes than popular the rg-normalised algorithm

Correspondence search in the presence of specular highlights using specular-free two-band images

Abstract. In this paper, we present a new method to deal with specular highlights in correspondence search. The proposed method is essentially based on the specular-free two-band image that we introduce to deal with specular reflection. For given input images, specular-free two-band images are generated using simple pixel-wise computations in real-time. Specular-free two-band images are then used to compute per-pixel raw matching costs. By using the specular-free two-band images instead of input images, reliable raw matching costs that are independent of the specularities of image pixels are obtained. As a result, we can find correct correspondences even in the presence of specular highlights. Experimental results show that the proposed method successfully produces accurate disparity maps for stereo images with specular highlights.

Highlight and Shading Invariant Color Image Segmentation Using Simulated Annealing

Abstract. Color constancy in color image segmentation is an impor-tant research issue. In this paper we develop a framework, based on the Dichromatic Re ection Model for asserting the color highlight and shading invariance, and based on a Markov Random Field approach for segmentation. A given RGB image is transformed into a R'G'B ' space to remove any highlight components, and only the vector-angle component, representing color hue but not intensity, is preserved to remove shading eects. Due to the arbitrariness of vector angles for low R'G'B ' values, we perform a Monte-Carlo sensitivity analysis to determine pixel-dependent weights for the MRF segmentation. Results are presented and analyzed.

Using Saliency-based Visual Attention Methods for Achieving Illumination Invariance in Robot Soccer

Abstract. In order to be able to beat the world champion human soccer team in the year 2050, soccer playing robots will need to have very robust vision systems that can cope with drastic changes in illumination conditions. However, the current vision systems are still brittle and they require exhaustive and repeated color calibration procedures to perform acceptably well. In this paper, we investigate the suitability of biologically inspired saliency-based visual attention models for developing robust vision systems for soccer playing robots while focusing on the illumination invariance aspect of the solution. The experiment results demonstrate successful and accurate detection of the ball even when the illumination conditions change continuously and dramatically.