Selective and robust perception using multiresolution estimation techniques

Data and model-driven processes are basic to image understanding systems and correspond preattentive and focal attentive processes, respectively. The authors describe how to develop preattentive and focal attentive processes primed by known object models complementary to efforts on data driven preattentive processes. The techniques used to implement attentional mechanisms are shown to be robust with respect to noise given as changes in illumination, able to reduce crosstalk and able to count outliers