A color projection for fast generic target tracking

We present a piecewise linear projection of the 3D color space that greatly reduces the computations required for using color information for robot vision tasks which we call categorical color. This 24-bit to 6-bit projection is inspired by the way humans name colors. This projection is developed to provide generic target tracking in real-time. A generic target in our system is defined by a user selecting a distinctive object in the window of a color image. The system has no a priori models of object shapes or colors. Therefore, the generic target tracking must perform robustly, in real time, using only the initial example appearance of the target object. To evaluate the performance of our piecewise linear projection on the task of generic target tracking, we compare similar RGB, intensity, and categorical color algorithms. Rather than simply observing the located target, we have developed a quantitative method for evaluating generic target tracking algorithms. By using this procedure, we show that categorical color is a better feature for generic tracking than RGB and gray-level