Finding Waldo, or focus of attention using local color information

" MR physics based snake tracking and dense deformations of tagged nu cardiac images, " AAA1 Using dynamic programming for solving variational problems in vision, " IEEE Truns. Puttern Analysis und Muchine Intelligence, pp. 855-867, 1990. R.A. Brooks, " Model-based three-dimensional interpretations of two-dimensional images, " IEEE Truns. Pattern Analysis und Muchine In-Tracing deformable objects in the plane using an active contour model,'' IEEE Trans. Puttern Anulysis und Mu-A fast algorithm for active contours and curvature estimation, " Abstract-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 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 Backpro-jection 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.