Boutros, Fadi ; Damer, Naser ; Terhörst, Philipp ; Kirchbuchner, Florian ; Kuijper, Arjan (2019)
Exploring the Channels of Multiple Color Spaces for Age and Gender Estimation from Face Images.
22nd International Conference on Information Fusion (FUSION). Ottawa, Canada (02.07.2019-05.07.2019)
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Soft biometrics identify certain traits of individuals based on their sampled biometric characteristics. The automatic identification of traits like age and gender provides valuable information in applications ranging from forensics to service personalization. Color images are stored within a color space containing different channels. Each channel represents a different portion of the information contained in the image, including these of soft biometric patterns. The analysis of the age and gender information in the different channels and different color spaces was not previously studied. This work discusses the soft biometric performances using these channels and analyzes the sample error overlap between all possible channels to successfully prove that different information is considered in the decision making from each channel. We also present a multi-channel selection protocols and fusion solution of the selected channels. Beside the analyzes of color spaces and their channels, our proposed multi-channel fusion solution extends beyond state-of-the-art performance in age estimation on the widely used Adience dataset.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2019 |
| Autor(en): | Boutros, Fadi ; Damer, Naser ; Terhörst, Philipp ; Kirchbuchner, Florian ; Kuijper, Arjan |
| Art des Eintrags: | Bibliographie |
| Titel: | Exploring the Channels of Multiple Color Spaces for Age and Gender Estimation from Face Images |
| Sprache: | Englisch |
| Publikationsjahr: | 2019 |
| Veranstaltungstitel: | 22nd International Conference on Information Fusion (FUSION) |
| Veranstaltungsort: | Ottawa, Canada |
| Veranstaltungsdatum: | 02.07.2019-05.07.2019 |
| URL / URN: | https://www.fusion2019.org/program.html |
| Kurzbeschreibung (Abstract): | Soft biometrics identify certain traits of individuals based on their sampled biometric characteristics. The automatic identification of traits like age and gender provides valuable information in applications ranging from forensics to service personalization. Color images are stored within a color space containing different channels. Each channel represents a different portion of the information contained in the image, including these of soft biometric patterns. The analysis of the age and gender information in the different channels and different color spaces was not previously studied. This work discusses the soft biometric performances using these channels and analyzes the sample error overlap between all possible channels to successfully prove that different information is considered in the decision making from each channel. We also present a multi-channel selection protocols and fusion solution of the selected channels. Beside the analyzes of color spaces and their channels, our proposed multi-channel fusion solution extends beyond state-of-the-art performance in age estimation on the widely used Adience dataset. |
| Freie Schlagworte: | Biometric fusion Biometrics Face recognition |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme 20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing |
| Hinterlegungsdatum: | 17 Apr 2020 10:05 |
| Letzte Änderung: | 17 Apr 2020 10:05 |
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