TARGET ATTRACTIVENESS MODEL FOR FIELD-OF-VIEW SEARCH

A target attractiveness model describes field-of-view search as a two- step process. The observer first decides to move to some location base d on its attraction and size. These attractive points are further divi ded by a second decision, which determines whether an observer will pe rform a detailed examination of the area or-will choose a new attracti ve point. Simple metrics based on preattentive vision processes such a s a probability of edge (POE) metric or the peak signal are used to re present the attractiveness. The model is tested on human performance e xperiments performed by the Night Vision and Electronic Sensors Direct orate, which provided eyetracker data for a series of static field-of- view images. The model predicts the statistical properties of the eyet racker points associated with the saccades, attractive points, and the examinations. The model predicts a clear statistical distinction betw een these points based on the distribution of the attractive metric in the image. In the simplest case considered, the saccade points are sh own to be random with respect to the image (distribution of attractive ness equivalent to whole image) while the attractive points and examin ations have distributions weighted by the first and second power of th e attractiveness, respectively. (C) 1998 Society of Photo-Optical Inst rumentation Engineers.