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In recent years, increasing deployment of face recognition technology insecurity-critical settings, such as border control or law enforcement, has ledto considerable interest in the vulnerability of face recognition systems toattacks utilising legitimate documents, which are issued on the basis ofdigitally manipulated face images. As automated manipulation and attackdetection remains a challenging task, conventional processes with humaninspectors performing identity verification remain indispensable. Thesecircumstances merit a closer investigation of human capabilities in detectingmanipulated face images, as previous work in this field is sparse and oftenconcentrated only on specific scenarios and biometric characteristics.  This work introduces a web-based, remote visual discrimination experiment onthe basis of principles adopted from the field of psychophysics andsubsequently discusses interdisciplinary opportunities with the aim ofexamining human proficiency in detecting different types of digitallymanipulated face images, specifically face swapping, morphing, and retouching.In addition to analysing appropriate performance measures, a possible metric ofdetectability is explored. Experimental data of 306 probands indicate thatdetection performance is widely distributed across the population and detectionof certain types of face image manipulations is much more challenging thanothers.

Psychophysical Evaluation of Human Performance in Detecting Digital Face Image Manipulations