Deep Fusion Siamese Network for Automatic Kinship Verification
2020 15th IEEE Conference on Automatic Face and Gesture Recognition; 4th Recognizing Families In the Wild (RFIW) Automatic kinship verification aims to determine whether some individuals belong to the same family. It is of great research significance to help missing persons reunite with their famili...
Saved in:
Main Authors | , , , |
---|---|
Format | Journal Article |
Language | English |
Published |
29.05.2020
|
Subjects | |
Online Access | Get full text |
DOI | 10.48550/arxiv.2006.00143 |
Cover
Summary: | 2020 15th IEEE Conference on Automatic Face and Gesture
Recognition; 4th Recognizing Families In the Wild (RFIW) Automatic kinship verification aims to determine whether some individuals
belong to the same family. It is of great research significance to help missing
persons reunite with their families. In this work, the challenging problem is
progressively addressed in two respects. First, we propose a deep siamese
network to quantify the relative similarity between two individuals. When given
two input face images, the deep siamese network extracts the features from them
and fuses these features by combining and concatenating. Then, the fused
features are fed into a fully-connected network to obtain the similarity score
between two faces, which is used to verify the kinship. To improve the
performance, a jury system is also employed for multi-model fusion. Second, two
deep siamese networks are integrated into a deep triplet network for
tri-subject (i.e., father, mother and child) kinship verification, which is
intended to decide whether a child is related to a pair of parents or not.
Specifically, the obtained similarity scores of father-child and mother-child
are weighted to generate the parent-child similarity score for kinship
verification. Recognizing Families In the Wild (RFIW) is a challenging kinship
recognition task with multiple tracks, which is based on Families in the Wild
(FIW), a large-scale and comprehensive image database for automatic kinship
recognition. The Kinship Verification (track I) and Tri-Subject Verification
(track II) are supported during the ongoing RFIW2020 Challenge. Our team
(ustc-nelslip) ranked 1st in track II, and 3rd in track I. The code is
available at https://github.com/gniknoil/FG2020-kinship. |
---|---|
DOI: | 10.48550/arxiv.2006.00143 |