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Subjective evaluation of high dynamic range imaging for face matching
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Suma, Rossella, Debattista, Kurt, Watson, Derrick G., Blagrove, Elisabeth and Chalmers, Alan (2019) Subjective evaluation of high dynamic range imaging for face matching. IEEE Transactions on Emerging Topics in Computing . doi:10.1109/TETC.2019.2958738 (In Press)
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WRAP-subjective-evaluation-high-dynamic-range-imaging-face-matching-Debattista-2019.pdf - Accepted Version - Requires a PDF viewer. Download (13Mb) | Preview |
Official URL: http://dx.doi.org/10.1109/TETC.2019.2958738
Abstract
Human facial recognition in the context of surveillance, forensics and photo-ID verification is a task for which accuracy is critical. Quite often limitations in the overall quality of facial images reduces individuals' ability in taking decisions regarding a person's identity. To verify the suitability of advanced imaging techniques to improve individuals' performance in face matching we investigate how High Dynamic Range (HDR) imaging compares with traditional low (or standard) dynamic range (LDR) imaging in a facial recognition task. An HDR face dataset with five different lighting conditions is created. Subsequently, this dataset is used in a controlled experiment (N=40) to measure performance and accuracy of human participants when identifying faces in HDR vs LDR. Results demonstrate that face matching accuracy and reaction time are improved significantly by HDR imaging. This work demonstrates scope for realistic image reproduction and delivery in face matching tasks and suggests that security systems could benefit from the adoption of HDR imaging techniques.
| Item Type: | Journal Article | ||||||
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| Subjects: | B Philosophy. Psychology. Religion > BF Psychology T Technology > TR Photography |
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| Divisions: | Faculty of Science > Psychology Faculty of Science > WMG (Formerly the Warwick Manufacturing Group) |
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| Library of Congress Subject Headings (LCSH): | High dynamic range imaging, Face perception -- Research, Face -- Imaging | ||||||
| Journal or Publication Title: | IEEE Transactions on Emerging Topics in Computing | ||||||
| Publisher: | IEEE | ||||||
| ISSN: | 2168-6750 | ||||||
| Official Date: | 9 December 2019 | ||||||
| Dates: |
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| Date of first compliant deposit: | 17 December 2019 | ||||||
| DOI: | 10.1109/TETC.2019.2958738 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | In Press | ||||||
| Publisher Statement: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| RIOXX Funder/Project Grant: |
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