Hand-drawn face sketch recognition using rank-level fusion of image quality assessment metrics
Face Sketch Recognition (FSR) presents a severe challenge to conventional recognition paradigms developed basically to match face photos. This challenge is mainly due to the large texture discrepancy between face sketches, characterized by shape exaggeration, and face photos. In this paper, we propo...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , |
| منشور في: |
2022
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://depot.sorbonne.ae/handle/20.500.12458/1320 |
| الوسوم: |
إضافة وسم
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| _version_ | 1857415063939317760 |
|---|---|
| author | Hadid, Abdenour |
| author2 | Mahfoud, Sami Daamouche, Abdelhamid Bengherabi, Messaoud |
| author2_role | author author author |
| author_facet | Hadid, Abdenour Mahfoud, Sami Daamouche, Abdelhamid Bengherabi, Messaoud |
| author_role | author |
| dc.creator.none.fl_str_mv | Hadid, Abdenour Mahfoud, Sami Daamouche, Abdelhamid Bengherabi, Messaoud |
| dc.date.none.fl_str_mv | 2022-11-03T05:23:08Z 2022-11-03T05:23:08Z 2022 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | 10.24425/bpasts.2022.DOI https://depot.sorbonne.ae/handle/20.500.12458/1320 10.24425/bpasts.2022.143554 |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | Bulletin of Polish Academy of Sciences Technical Sciences |
| dc.subject.none.fl_str_mv | Face sketch recognition Synthesized face sketch Rank-level fusion IQA metrics |
| dc.title.none.fl_str_mv | Hand-drawn face sketch recognition using rank-level fusion of image quality assessment metrics |
| dc.type.none.fl_str_mv | Controlled Vocabulary for Resource Type Genres::text::periodical::journal::contribution to journal::journal article |
| description | Face Sketch Recognition (FSR) presents a severe challenge to conventional recognition paradigms developed basically to match face photos. This challenge is mainly due to the large texture discrepancy between face sketches, characterized by shape exaggeration, and face photos. In this paper, we propose a training-free synthesized face sketch recognition method based on the rank-level fusion of multiple Image Quality Assessment (IQA) metrics. The advantages of IQA metrics as a recognition engine are combined with the rank level fusion to boost the final recognition accuracy. By integrating multiple IQA metrics into the face sketch recognition framework, the proposed method simultaneously performs face-sketch matching application and evaluates the performance of face sketch synthesis methods. To test the performance of the recognition framework, five synthesized face sketch methods are used to generate sketches from face photos. We use the Borda count approach to fuse four IQA metrics, namely, structured similarity index metric, feature similarity index metric, visual information fidelity and gradient magnitude similarity deviation at the rank-level. Experimental results and comparison with the state-of-the-art methods illustrate the competitiveness of the proposed synthesized face sketch recognition framework. |
| id | sorbonner_d134588d9d583b3e33b09d4533f75af0 |
| identifier_str_mv | 10.24425/bpasts.2022.DOI 10.24425/bpasts.2022.143554 |
| language_invalid_str_mv | en |
| network_acronym_str | sorbonner |
| network_name_str | Sorbonne University Abu Dhabi repository |
| oai_identifier_str | oai:depot.sorbonne.ae:20.500.12458/1320 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Hand-drawn face sketch recognition using rank-level fusion of image quality assessment metricsHadid, AbdenourMahfoud, SamiDaamouche, AbdelhamidBengherabi, MessaoudFace sketch recognitionSynthesized face sketchRank-level fusionIQA metricsFace Sketch Recognition (FSR) presents a severe challenge to conventional recognition paradigms developed basically to match face photos. This challenge is mainly due to the large texture discrepancy between face sketches, characterized by shape exaggeration, and face photos. In this paper, we propose a training-free synthesized face sketch recognition method based on the rank-level fusion of multiple Image Quality Assessment (IQA) metrics. The advantages of IQA metrics as a recognition engine are combined with the rank level fusion to boost the final recognition accuracy. By integrating multiple IQA metrics into the face sketch recognition framework, the proposed method simultaneously performs face-sketch matching application and evaluates the performance of face sketch synthesis methods. To test the performance of the recognition framework, five synthesized face sketch methods are used to generate sketches from face photos. We use the Borda count approach to fuse four IQA metrics, namely, structured similarity index metric, feature similarity index metric, visual information fidelity and gradient magnitude similarity deviation at the rank-level. Experimental results and comparison with the state-of-the-art methods illustrate the competitiveness of the proposed synthesized face sketch recognition framework.2022-11-03T05:23:08Z2022-11-03T05:23:08Z2022Controlled Vocabulary for Resource Type Genres::text::periodical::journal::contribution to journal::journal articleapplication/pdf10.24425/bpasts.2022.DOIhttps://depot.sorbonne.ae/handle/20.500.12458/132010.24425/bpasts.2022.143554enBulletin of Polish Academy of SciencesTechnical Sciencesoai:depot.sorbonne.ae:20.500.12458/13202023-01-26T06:49:48Z |
| spellingShingle | Hand-drawn face sketch recognition using rank-level fusion of image quality assessment metrics Hadid, Abdenour Face sketch recognition Synthesized face sketch Rank-level fusion IQA metrics |
| title | Hand-drawn face sketch recognition using rank-level fusion of image quality assessment metrics |
| title_full | Hand-drawn face sketch recognition using rank-level fusion of image quality assessment metrics |
| title_fullStr | Hand-drawn face sketch recognition using rank-level fusion of image quality assessment metrics |
| title_full_unstemmed | Hand-drawn face sketch recognition using rank-level fusion of image quality assessment metrics |
| title_short | Hand-drawn face sketch recognition using rank-level fusion of image quality assessment metrics |
| title_sort | Hand-drawn face sketch recognition using rank-level fusion of image quality assessment metrics |
| topic | Face sketch recognition Synthesized face sketch Rank-level fusion IQA metrics |
| url | https://depot.sorbonne.ae/handle/20.500.12458/1320 |