Finding Waldo, or focus of attention using local color information

We present a method to locate an “object” in a color image, or more precisely, to select a set of likely locations for the object. The model is assumed to be of known color distribution, which permits the use color-space processing. A new method is presented, which exploits more information than the previous backprojection algorithm of Swain and Ballard (1990) at a competitive complexity. Precisely, the new algorithm is based on matching local histograms with the model, instead of directly replacing pixels with a confidence that they belong to the object. We prove that a simple version of this algorithm degenerates into backprojection in the worst case. In addition, we show how to estimate the scale of the model. Results are shown on pictures digitized from the famous “Where is Waldo” books. Issues concerning the optimal choice of a color space and its quantization are carefully considered and studied in this application. We also propose to use co-occurrence histograms to deal with cases where important color variations can be expected