Abstract
In this paper, we propose an adaptive color extraction technique employing an update type two-dimensional color histogram model. A two-dimensional color histogram model using an H-S plane in the HSV color space is updated every time, and it extracts object's color that varies under changeable illumination. When updating the color model, color of the background area might be included in a color model as a noise. By such a miss update, a color model will be overflowed with non-object's colors. We define an asymmetric anisotropic Gaussian-like distribution in order to estimate a changeable color area of an object, and employ it as kernel function for providing weight coefficients to the model update. We have developed a color tracking system using a pan-tilt camera, and performed tracking experiments in two different environments, i.e., an indoor environment with changeable illumination and an outdoor environment under sunshine. As a result, the developed system kept tracking an object successfully even though the illumination has changed in both environments.
