Advances in Modeling Visual Search and Target Discrimination Performance

This paper reports on advances in mathematical models of observer-ensemble performance in narrow-field- of-view visual search and target discrimination for ground vehicles in natural terrain. Three developments are presented. We show that the distribution of search time follows a log normal distribution. We show that search outcome is the result of a race between scene parsing and target detection. Scene parsing guides and focuses search, but also leads to quitting without detection. Quitting is not simply the consequence of having exhausted the supply of suspect locations. We present a refined target signature metric and computational method that emulates human perceptual organization of the target into component regions. This is significant not only because it improves the ease-of-use and reduces subjective user input, but also because it is potentially applicable to thermal images. The refined metric provides reasonably accurate prediction of probability of detection for cued detection and uncued search experiments.
Presented at the Ground Target Modeling and Validation Conference (13th) held in Houghton, MI on 5-8 Aug 2002. Published in the Proceedings of the Ground Target Modeling and Validation Conference (13th), 247-256, 2002. This article is from ADA459530 Proceedings of the Ground Target Modeling and Validation Conference (13th) Held in Houghton, MI on 5-8 August 2002