Abstract

Low‐quality images are problematic for face identification, for example, when the
police identify faces from CCTV images. Here, we test whether face averages, comprising
multiple poor‐quality images, can improve both human and computer recognition.
We created averages from multiple pixelated or nonpixelated images and
compared accuracy using these images and exemplars. To provide a broad assessment
of the potential benefits of this method, we tested human observers (n = 88; Experiment
1), and also computer recognition, using a smartphone application (Experiment
2) and a commercial one‐to‐many face recognition system used in forensic settings
(Experiment 3). The third experiment used large image databases of 900 ambient
images and 7,980 passport images. In all three experiments, we found a substantial
increase in performance by averaging multiple pixelated images of a person's face.
These results have implications for forensic settings in which faces are identified from
poor‐quality images, such as CCTV