The effect of selective spatial attention on peripheral discrimination thresholds

Experiments were conducted to investigate the role of attention in peripheral detection and discrimination. Advance spatial cues informed subjects about likely target positions; the task required to detect/discriminate plus localise a target briefly presented at cued or uncued locations, with accuracy as the dependent variable ("cost-benefit" analysis).Spatial cueing produced reliable advantages for cued over uncued locations, in single and in multiple element displays. However, costs plus benefits were less marked for single displays. Thus, advance knowledge of the likely target location enhances performance also when there are no competing stimuli present in the visual field. But costs plus benefits are smaller because single target onsets at uncued locations summon attention in the same "automatic" fashion as peripheral cues. Peripheral cues trigger a rapid facilitatory component (automatic), fading out within 300 msec after cue onset. Facilitation is then maintained by a less effective mechanism (controlled). Central cues initiate only this second component. Sustained, controlled, orienting in response to central cues is interruptable by automatic orienting in response to uninformative peripheral flashes. Interruption also occurs when irrelevant flashes compete with peripheral cues. However, interference is less marked for the early automatic than for the following controlled orienting component. Indication of a second position (four-location display) to be most likely resulted in a marked sensitivity gain for this position, relative to uncued locations in a single cue condition. That is, attention could be simultaneously shared between two cued positions. For a luminance detection task (single target), cued locations showed no advantage in sensitivity; but for letter detection tasks (target plus distractors), there was a marked priming effect. That is, letter detection is capacity limited, whereas luminance detection is not. In all tasks, decision criteria are largely preset according to a-priori target probabilities assigned to particular locations, i.e. more liberal for cued and more conservative for uncued locations

Shape classification: towards a mathematical description of the face

Recent advances in biostereometric techniques have led to the quick and easy acquisition of 3D data for facial and other biological surfaces. This has led facial surgeons to express dissatisfaction with landmark-based methods for analysing the shape of the face which use only a small part of the data available, and to seek a method for analysing the face which maximizes the use of this extensive data set. Scientists working in the field of computer vision have developed a variety of methods for the analysis and description of 2D and 3D shape. These methods are reviewed and an approach, based on differential geometry, is selected for the description of facial shape. For each data point, the Gaussian and mean curvatures of the surface are calculated. The performance of three algorithms for computing these curvatures are evaluated for mathematically generated standard 3D objects and for 3D data obtained from an optical surface scanner. Using the signs of these curvatures, the face is classified into eight 'fundamental surface types' - each of which has an intuitive perceptual meaning. The robustness of the resulting surface type description to errors in the data is determined together with its repeatability. Three methods for comparing two surface type descriptions are presented and illustrated for average male and average female faces. Thus a quantitative description of facial change, or differences between individual's faces, is achieved. The possible application of artificial intelligence techniques to automate this comparison is discussed. The sensitivity of the description to global and local changes to the data, made by mathematical functions, is investigated. Examples are given of the application of this method for describing facial changes made by facial reconstructive surgery and implications for defining a basis for facial aesthetics using shape are discussed. It is also applied to investigate the role played by the shape of the surface in facial recognition