Test of three visual search and detection models

Advance knowledge of the time required by an observer to detect a target vi sually is of interest, e.g., in preparing flight scenarios, in modeling mis sion performance, in evaluating camouflage effectiveness, and in visual-sce ne generator calibration. A wide range of computational models has therefor e been developed to predict human visual search and detection performance. This study is performed to test the quality of the predictions of three of these models: ORACLE, Visdet, and a formula by Travnikova. The three differ ent models are used to predict the results of an experiment in which observ ers searched for military vehicles in complex rural scenes. The models pred ict either the mean time required to find the target, or the probability of finding the target after a given amount of time, from a few physical param eters describing the scene (the mean scene luminance, the angular dimension s of the field of view and the target, the intrinsic target contrast, etc.) . None of the models reliably predicts observer performance for most of the scenes used in this study. ORACLE and Visdet both overestimate the detecti on probability for most situations. The formula by Travnikova does not appl y to the scenes used here. (C) 2000 Society of Photo-Optical Instrumentatio n Engineers.