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Machine Vision and Applications
Erschienen in: Machine Vision and Applications 4/2014

01.05.2014 | Original Paper

Family verification based on similarity of individual family member’s facial segments

verfasst von: Mohammad Ghahramani, Wei-Yun Yau, Eam Khwang Teoh

Erschienen in: Machine Vision and Applications | Ausgabe 4/2014

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Abstract

Humans process faces to recognize family resemblance and act accordingly. Undoubtedly, they are capable of recognizing their kin and family members. In this paper, we study the facts and valid assumptions of facial resemblance in family members’ facial segments. Our analysis and psychological studies show that the facial resemblance differs from member to member and depends on image segments. First, we estimate the degree of resemblance of each member’s image segment. Then, we propose a novel method to fuse similarity of each member’s facial image segments to perform family verification. Employing the proposed approach on the collected 5,400-sample family database achieves considerable improvement compared to the state-of-the-art fusion rule in three designated test scenarios. Experimental results also show that the proposed approach could estimate the similarity slightly more accurate than human perception. We believe the public availableness of the database may advance the development in this domain.
Vorheriger Artikel OPTIMUS:online persistent tracking and identification of many users for smart spaces
Nächster Artikel Kernelized pyramid nearest-neighbor search for object categorization

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Metadaten
Titel
Family verification based on similarity of individual family member’s facial segments
verfasst von
Mohammad Ghahramani
Wei-Yun Yau
Eam Khwang Teoh
Publikationsdatum
01.05.2014
Verlag
Springer Berlin Heidelberg
Erschienen in
Machine Vision and Applications / Ausgabe 4/2014
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-013-0566-1

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