title: Cube search, revisited.
abstract: Observers can quickly search among shaded cubes for one lit from a unique direction. However, replace the cubes with similar 2-D patterns that do not appear to have a 3-D shape, and search difficulty increases. These results have challenged models of visual search and attention. We demonstrate that cube search displays differ from those with "equivalent" 2-D search items in terms of the informativeness of fairly low-level image statistics. This informativeness predicts peripheral discriminability of target-present from target-absent patches, which in turn predicts visual search performance, across a wide range of conditions. Comparing model performance on a number of classic search tasks, cube search does not appear unexpectedly easy. Easy cube search, per se, does not provide evidence for preattentive computation of 3-D scene properties. However, search asymmetries derived from rotating and/or flipping the cube search displays cannot be explained by the information in our current set of image statistics. This may merely suggest a need to modify the model's set of 2-D image statistics. Alternatively, it may be difficult cube search that provides evidence for preattentive computation of 3-D scene properties. By attributing 2-D luminance variations to a shaded 3-D shape, 3-D scene understanding may slow search for 2-D features of the target.
authors.affiliation: Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China.
authors.forename: Xuetao
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors.forename: Jie
authors.initials: J
authors.lastname: Huang
authors.affiliation: Exponent, Bellevue, WA, USA.
authors.forename: Serap
authors.initials: S
authors.lastname: Yigit-Elliott
authors.affiliation: Department of Brain and Cognitive Sciences, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors.forename: Ruth
authors.initials: R
authors.lastname: Rosenholtz
mesh_terms: D005556:Form Perception / Q000502:physiology*; D006801:Humans; D021621:Imaging, Three-Dimensional; D010364:Pattern Recognition, Visual / Q000502:physiology*; D011601:Psychophysics
keywords: 3-D shape; Feature Integration Theory; Texture Tiling Model; familiarity; image statistics; lighting direction; mongrel; peripheral vision; summary statistics; visual search