The targets for saccadic eye movements in natural visual scenes are spatially extended objects, yet saccades land at a single position within them. To characterize the spatial transformation that determines the saccadic goal position within attended objects, we studied saccadic localization of large patterns of random dots. Saccades landed with a high degree of precision near the center-of-gravity of the patterns (average error < 10%; SDs around the center-of-gravity = 7-11% of target eccentricity). Predictions of landing position were improved by using a weighted center-of-gravity, in which the weight assigned to each dot was reduced by the presence of neighboring dots. Weighting based either on the eccentricity of dots or their position relative to the boundary of the pattern had no effect. The results can be accounted for by a spatial transformation in which the "local signs" of an initial array of detectors, weighted by the activity of each, are averaged to yield the saccadic goal. This model can account for accurate and precise saccadic localization of large targets, while preserving sensitivity to local pattern characteristics. Unlike models of recognition, the boundary of the object has the same status as the internal details.