سال انتشار:

2021

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عنوان انگلیسی مقاله:

Multi-view discriminant analysis with sample diversity for ECG biometric recognition

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ترجمه فارسی عنوان مقاله:

تجزیه و تحلیل تشخیص چند دیدگاهی با تنوع نمونه برای تشخیص بیومتریک ECG

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منبع:

Sciencedirect - Elsevier - Pattern Recognition Letters, 145 (2021) 110-117: doi:10:1016/j:patrec:2021:01:027

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نویسنده:

Yuwen Huang

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چکیده انگلیسی:

Soft biometrics, although not discriminant enough for person recognition provides additional information that aids traditional person recognition. Initially, attempts were made to integrate appearance-based facial soft biometrics, such as facial marks, skin color, and hair color/style, but more recently behavior based facial soft biometrics, such as head dynamics, visual speech, and facial expressions have also been studied. Facial expressions are further classified as macro and micro-expressions and most of the existing studies using facial expressions as a soft biometric have focused on macro-expressions. Therefore, in this study, we investigate the utility of micro-expressions as a soft biometric for person recognition. The proposed system is based on the fusion of traditional facial features that model the facial appearance with soft biometric features that model the micro-expressions in an image sequence. We tested a texture based traditional feature extraction technique, two motion-based soft biometric techniques, and several fusion methods at feature, rank, and decision level. The experiments were conducted on three commonly used micro-expression databases and exhibit an improvement of around 5% identification rate when soft biometric traits are fused with traditional face recognition at decision level.
Keywords: Person recognition | Multi-modal biometrics | Soft biometrics | Micro-expressions

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قیمت: رایگان

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توضیحات اضافی:

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