Deep multi-person kinship matching and recognition for family photos
作者：
Highlights：
• First, we design a deep kinship matching and recognition (DKMR) framework for understanding kinship in a nuclear family automatically. It makes the first attempt to generate a nuclear family tree end-to-end, to our best knowledge.
• Second, compared with previous kinship understanding methods focusing on pairwise face images, 70 the input of our DKMR framework extends to one nuclear family photo. The experiments on Group-Face, TSkinFace and FIW datasets demonstrate its effectiveness.
• Third, our proposed reasoning conditional random field (R-CRF) algorithm fully exploits the common kinship rules to well boost matching and recognition accuracy and ensure the output family tree is optimal.
摘要
•First, we design a deep kinship matching and recognition (DKMR) framework for understanding kinship in a nuclear family automatically. It makes the first attempt to generate a nuclear family tree end-to-end, to our best knowledge.•Second, compared with previous kinship understanding methods focusing on pairwise face images, 70 the input of our DKMR framework extends to one nuclear family photo. The experiments on Group-Face, TSkinFace and FIW datasets demonstrate its effectiveness.•Third, our proposed reasoning conditional random field (R-CRF) algorithm fully exploits the common kinship rules to well boost matching and recognition accuracy and ensure the output family tree is optimal.
论文关键词：Kinship matching and recognition,Deep learning,R-CRF Algorithm
论文评审过程：Received 16 November 2019, Revised 22 February 2020, Accepted 17 March 2020, Available online 28 March 2020, Version of Record 5 June 2020.
论文官网地址：https://doi.org/10.1016/j.patcog.2020.107342
