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Thesis (MEng) -- Stellenbosch University, 2022.
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| Other Authors: | |
| Format: | Thesis |
| Language: | en_ZA |
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Stellenbosch : Stellenbosch University
2022
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| _version_ | 1867614038816456704 |
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| access_status_str | Open Access |
| author | Muthua, Alex |
| author2 | Theart, Rensu |
| author_browse | Muthua, Alex Theart, Rensu |
| author_facet | Theart, Rensu Muthua, Alex |
| author_sort | Muthua, Alex |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MEng) -- Stellenbosch University, 2022. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/126005 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:45:41.741Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/126005 What the eye doesn’t see : using infrared to improve face recognition of individuals with highly pigmented skin Muthua, Alex Theart, Rensu Booysen, Thinus Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. Infrared spectroscopy Human face recognition (Computer science) Computers -- Access control Human skin color UCTD Thesis (MEng) -- Stellenbosch University, 2022. ENGLISH ABSTRACT: Face recognition technology has become commonplace in security and access control applications. However, their performance leaves a lot to be desired when working with highly pigmented skin tones. One reason for this is the training bias introduced by under-representation in existing datasets. The other is inherent to pigmentation – darker skins absorb more light and therefore could reflect l ess d iscernible d etail i n t he v isible s pectrum. We s how how this can be enhanced by incorporating the infrared spectrum, which electronic sensors can perceive. We collect a database with images of highly pigmented individuals, captured using the visible, infrared and full spectra We fine-tune state-of-the-art face recognition systems and compare the performance of these three spectra. We also assess the impact of narrow and wide cropping, different facial orientations, and sunlit and shaded conditions. We find a marked improvement in the accuracy and in the AUC values of the ROC curves when including the infrared spectrum, with performance increasing from 97.5% to 99.1% for highly pigmented faces. Including different facial orientations and narrow cropping also improves the performance, and can therefore be deemed as recommended best practices. Analysis of the activation maps of the CNNs finds t hat fi ne-tuning mo dels ac tivate mo re ge nerally ov er al l re gions of the face while models with pre-trained weights, focus on fewer features with higher activation intensity values over those regions. In both cases, the nose region appears as the most important feature for face recognition for highly pigmented faces. Masters 2022-11-16T06:58:17Z 2023-01-16T12:45:16Z 2022-11-16T06:58:17Z 2023-01-16T12:45:16Z 2022-12 Thesis http://hdl.handle.net/10019.1/126005 en_ZA Stellenbosch University xi, 113 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Infrared spectroscopy Human face recognition (Computer science) Computers -- Access control Human skin color UCTD Muthua, Alex What the eye doesn’t see : using infrared to improve face recognition of individuals with highly pigmented skin |
| title | What the eye doesn’t see : using infrared to improve face recognition of individuals with highly pigmented skin |
| title_full | What the eye doesn’t see : using infrared to improve face recognition of individuals with highly pigmented skin |
| title_fullStr | What the eye doesn’t see : using infrared to improve face recognition of individuals with highly pigmented skin |
| title_full_unstemmed | What the eye doesn’t see : using infrared to improve face recognition of individuals with highly pigmented skin |
| title_short | What the eye doesn’t see : using infrared to improve face recognition of individuals with highly pigmented skin |
| title_sort | what the eye doesn t see using infrared to improve face recognition of individuals with highly pigmented skin |
| topic | Infrared spectroscopy Human face recognition (Computer science) Computers -- Access control Human skin color UCTD |
| url | http://hdl.handle.net/10019.1/126005 |
| work_keys_str_mv | AT muthuaalex whattheeyedoesntseeusinginfraredtoimprovefacerecognitionofindividualswithhighlypigmentedskin |