title: Predicting the probability of facial identification using a specific object model.
abstract: Many security and surveillance tasks involve either finding an object in a cluttered scene or discriminating between like objects. For example, an observer might look for a person of known height and weight in a crowd, or he might want to positively identify a specific face. The paper "Modeling target acquisition tasks associated with security and surveillance" [Appl. Opt. 46, 4209 (2007)] describes a specific-object model used to predict the probability of accomplishing this type of task. We describe four facial identification experiments and apply the specific-object model to predict the results. Facial identification is accurately predicted by the specific-object model.
authors.affiliation: 760 Jacktown Road, Lexington, Virginia 24450, USA.
authors.forename: Richard H
authors.initials: RH
authors.lastname: Vollmerhausen
authors.forename: Steve
authors.initials: S
authors.lastname: Moyer
authors.forename: Keith
authors.initials: K
authors.lastname: Krapels
authors.forename: Ronald G
authors.initials: RG
authors.lastname: Driggers
authors.forename: Jonathan G
authors.initials: JG
authors.lastname: Hixson
authors.forename: Aaron L
authors.initials: AL
authors.lastname: Robinson
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001699:Biometry / Q000379:methods*; D005145:Face / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008953:Models, Anatomic; D008954:Models, Biological; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique