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Automated kinship verification and identification through human facial images: a survey

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Abstract

Face is the most considerable constituent that people use to recognize one another. Humans can quickly and easily identify each other by their faces and since facial features are unobtrusive to lighting condition and pose, face remains as a dynamic recognition approach to human. Kinship recognition refers to the task of training a machine to recognize the blood relation between a pair of kin and non-kin faces (verification) based on features extracted from facial images, and to determine the exact type or degree of that relation (identification). Automatic kinship verification and identification is an interesting areas for investigation, and it has a significant impact in many real world applications, for instance, forensic, finding missing family members, and historical and genealogical research. However, kinship recognition is still not largely explored due to insufficient database availability. In this paper we present a survey on issues and challenges in kinship verification and identification, related previous works, current trends and advancements in kinship recognition, and potential applications and research direction for the future. We also found that Deep Learning (DL) has mostly outperformed numerous methods using manually designed features by automatically learning and extracting important information from facial features, and enable significant visual recognition functions by improving accuracy in most applications.

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Acknowledgments

I would like to express my special thanks of gratitude to the Saudi Ministry of Higher Education, Cultural Mission in Malaysia, UTM-Big Data Center as well as University Teknologi Malaysia (UTM) who gave me the golden opportunity to do this paper on the topic “Automated Kinship Verification and Identification Through Human Facial Images”, which also helped me in doing a lot of Research and I came to know about so many new things I am really thankful to them.

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Authors and Affiliations

  1. Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru, Malaysia

    Mohammed Almuashi & Dzulkifli Mohamad

  2. UTM-Big Data Center, Universiti Teknologi Malaysia, Johor Bahru, Malaysia

    Siti Zaiton Mohd Hashim & Aida Ali

  3. Faculty of Information Sciences and Engineering, Management and Science University, Selangor, Malaysia

    Mohammed Hazim Alkawaz

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  1. Mohammed Almuashi
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Correspondence to Mohammed Almuashi.

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Almuashi, M., Mohd Hashim, S.Z., Mohamad, D. et al. Automated kinship verification and identification through human facial images: a survey. Multimed Tools Appl 76, 265–307 (2017). https://doi.org/10.1007/s11042-015-3007-5

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