A model (SIAM) of the dynamic course of similarity comparisons is presented. According to SIAM, when structured scenes are compared, the parts of one scene must be aligned, or placed in correspondence, with the parts from the other scene. Emerging correspondences influence each other in a manner such that, with sufficient time, the strongest correspondences will be those that are globally consistent with other correspondences. Before these globally consistent correspondences emerge as the most active, similarity is considerably influenced by poorly aligned scene parts. Several predictions of SIAM are confirmed by three experiments on speeded comparisons of visual scenes. Relative to globally inconsistent feature matches, globally consistent feature matches influence similarity more when greater amounts of time are given for a comparison. A common underlying process model of scene alignment accounts for commonalities between different task conditions. Diffferences between task conditions are accounted for by principled parametric variation within the model. The empirical results and model simulations indicate that the comparison process often involves establishing consistent correspondences between scene parts, and that this alignment process has a characteristic time course.