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Journal ArticleDOI

Recent advances in facial soft biometrics

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TLDR
This paper presents state-of-the-art techniques in facial soft biometrics research by describing the type of traits, feature extraction methods, and the application domains, and indicates the most recent and valuable results attained.
Abstract
Face as a biometric attribute has been extensively studied over the past few decades. Even though, satisfactory results are already achieved in controlled environments, the practicality of face recognition in realistic scenarios is still limited by several challenges, such as, expression, pose, occlusion, etc. Recently, the research direction is concentrating on the prospects of complementing face recognition systems with facial soft biometric traits. The ease of extracting facial soft biometrics under several varying conditions has mainly resulted in the ability of using the traits to, either improve the performance of traditional face recognition systems, or performing recognition solely based on many facial soft biometrics. This paper presents state-of-the-art techniques in facial soft biometrics research by describing the type of traits, feature extraction methods, and the application domains. It indicates the most recent and valuable results attained, while also highlighting some possible future scientific research directions to be investigated.

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Citations
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Journal ArticleDOI

On soft biometrics

TL;DR: The achievements that have been made in recognition by and in estimation of these parameters are surveyed, describing how these approaches can be used and where they might lead to.
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Classical and modern face recognition approaches: a complete review

TL;DR: The prime objective of this research is to sum-up recent face recognition techniques and develop a broad understanding of how these techniques behave on different datasets and present future aspects of face recognition technologies and its potential significance in the upcoming digital society.
Journal ArticleDOI

Integration of multiple soft biometrics for human identification

TL;DR: The results show that the proposed framework can be utilized to model an adequate soft biometric system with rank-1 identification rate of 88%.
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Soft biometrics: a survey

TL;DR: The paper presents a detailed analysis on the global traits associated to person identity such as gender, age and ethnicity and a performance analysis of hybrid soft biometrics recognition system using multi-scale criterion.
Journal ArticleDOI

A Multi-Modal Person Recognition System for Social Robots

TL;DR: The paper presents a solution to the problem of person recognition by social robots via a novel brain-inspired multi-modal perceptual system that employs spiking neural network to integrate face, body features, and voice data to recognize a person in various social human-robot interaction scenarios.
References
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Journal ArticleDOI

Eigenfaces for recognition

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Journal ArticleDOI

Active shape models—their training and application

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TL;DR: In this paper, the authors provide an up-to-date critical survey of still-and video-based face recognition research, and provide some insights into the studies of machine recognition of faces.
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Journal ArticleDOI

An introduction to biometric recognition

TL;DR: A brief overview of the field of biometrics is given and some of its advantages, disadvantages, strengths, limitations, and related privacy concerns are summarized.
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