Enhancing CCTV: Averages improve face identification from poor‐quality images

Ritchie, Kay, White, David, Kramer, Robin , Noyes, Eilidh, Jenkins, Rob and Burton, A. Mike (2018) Enhancing CCTV: Averages improve face identification from poor‐quality images. Applied Cognitive Psychology, 32 (6). pp. 671-680. ISSN 0888-4080

Full content URL: https://doi.org/10.1002/acp.3449

Enhancing CCTV: Averages improve face identification from poor‐quality images
[img] Microsoft Word
Ritchie et al author copy.docx - Whole Document
Available under License Creative Commons Attribution-NonCommercial 4.0 International.

Item Type:Article
Item Status:Live Archive


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

Additional Information:The final published version of this article can be accessed online at https://onlinelibrary.wiley.com/doi/full/10.1002/acp.3449
Keywords:averages, CCTV, face identification, pixelated images
Subjects:C Biological Sciences > C810 Applied Psychology
C Biological Sciences > C800 Psychology
C Biological Sciences > C850 Cognitive Psychology
Divisions:College of Social Science > School of Psychology
ID Code:33018
Deposited On:23 Aug 2018 07:55

Repository Staff Only: item control page