RSFS: A soft biometrics-based relative support features set for person verification

Bilal Hassan; Ebroul Izquierdo

doi:10.1117/12.2644457

12 October 2022 RSFS: A soft biometrics-based relative support features set for person verification

Bilal Hassan, Ebroul Izquierdo

Proceedings Volume 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022); 1234202 (2022) https://doi.org/10.1117/12.2644457
Event: Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 2022, Wuhan, China

Abstract

Generally, biometrics is gaining increased attention due to its application for secure and efficient verification – more specifically at border crossing points. Usually, there are many different types of biometrics associated with human body i.e., intrusive like finger prints etc. and non-intrusive, termed as soft biometrics. In order to make the concept of Smart Borders a reality, the non-intrusive soft biometrics are the baseline technology. One of biggest challenge in soft biometrics based verification is to find a highly related set of features from different modalities of human body – as there is large number such soft biometrics associated with human body. In fact, this is extremely useful to select only those soft biometrics which are supportive to each other and relevant to the problem domain. In our work, we thoroughly investigated one of the largest collection of soft biometrics and developed a multiple non-linear regression based framework for the selection of highly supportive and relevant soft biometrics. We used one of the largest dataset e.g., PETA and its annotation for the evaluation of our proposed model. The accuracy is reported in form of MAE and error distribution graphs for two global soft biometrics i.e., gender and age prediction.

Citation Download Citation

Bilal Hassan and Ebroul Izquierdo "RSFS: A soft biometrics-based relative support features set for person verification", Proc. SPIE 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 1234202 (12 October 2022); https://doi.org/10.1117/12.2644457

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KEYWORDS

Biometrics

Data modeling

Feature extraction

Inspection

Skin

Head

Image resolution

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