Figure 1.

Comparison of two visual search models. (A) Rule of thumb for the traditional feature integration theory (FIT). FIT is a word-model that operates on descriptions of the target and distractor items. As such, it allows for easy intuitions, enabling design of new and interesting experiments. However, it is inherently under-specified without a complete description of basic features. (B) The texture tiling model (TTM). TTM is an image-computable model which takes as input image patches from the search display. Its features—a rich set of local image statistics—are fully specified. However, due to this complex set of features, TTM does not as easily lend itself to intuitions, making design of new experiments more difficult. Here we work to develop a TTM rule of thumb, to facilitate understanding of the model and intuitions about its predictions.