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    A novel approach for recognising people of the same family

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    Family members have certain facial resemblances due to genetic similarities. Such resemblance allows us to guess the family relationship which has received little attention to date. In this paper, we propose to recognise immediate members of the same family known as 'family verification' through identification of members' facial resemblance features. At first, the proposed operator extracts detailed facial information comparing to the state-of-the-art face descriptors. A novel redundant feature set removal is incorporated to reduce feature dimension. Experiments are conducted to compare performance of various features employing the proposed method and the state-of-the-art face recognition as well as the proposed redundant feature removal. The experiments also cover various scenarios where different members of the family are absent from training but present in the testing applied for missing family member verification. Results obtained show that the proposed approach is feasible even in case of missing member verification
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