title: Spatial summation of face information.
abstract: Do all parts of the face contribute equally to face detection or are some parts more detectable than others? To evaluate this issue, we studied detection of the presence of normalized frontal-face images within aperture windows of varying extent. We performed a face summation study using two-alternative forced-choice psychophysics. The face stimuli were scaled to equal eye-to-chin distance, centered on the bridge of the nose, and windowed by fourth-power Gaussian envelopes of various sizes. The faces were intermixed with control stimuli consisting inverted faces to test for configuration effects, split-half inverted faces to perturb the symmetry, and phase-scrambled versions of the faces with equal Fourier energy. Face detectability improved rapidly at first, then at a progressively shallower rate for larger window sizes, in a similar fashion for the three face-based stimulus types. The spectrally equated noise stimuli were less detectable than the face stimuli for all except the smallest apertures. The results were fit with a model incorporating global face-specific and local nonspecific spatial integration mechanisms. Detection of the noise images was consistent with local detection mechanisms accessed through a wide-field attention mechanism. The data for face detection implied detection mechanisms that integrated linearly up to some small size, integrated more slowly up to an intermediate size, and failed to gain any improvement for information beyond some larger size. This performance supports the concept of a specialized face configuration mechanism operating at detection threshold, similar in extent among the observers.
authors.affiliation: The Smith-Kettlewell Eye Research Institute, San Francisco, CA, USA. cwt@ski.org
authors.forename: Christopher W
authors.initials: CW
authors.lastname: Tyler
authors.forename: Chien-Chung
authors.initials: CC
authors.lastname: Chen
mesh_terms: D016477:Artifacts; D005145:Face; D005583:Fourier Analysis; D006801:Humans; D008960:Models, Psychological; D016011:Normal Distribution; D010364:Pattern Recognition, Visual; D011601:Psychophysics; D012684:Sensory Thresholds