Inheritable Fisher vector feature for kinship verification
Document Type
Conference Proceeding
Publication Date
12-16-2015
Abstract
An innovative inheritable Fisher vector feature (IFVF) method is presented in this paper for kinship verification. Specifically, Fisher vector is first derived for each image by aggregating the densely sampled SIFT features in the opponent color space. Second, a new inheritable transformation, which maximizes the similarity between kinship images while minimizes that between non-kinship images for each image pair simultaneously, is learned based on the Fisher vectors. As a result, the IFVF is derived by applying the inheritable transformation on the Fisher vector for each image. Finally, a novel fractional power cosine similarity measure, which shows its theoretical roots in the Bayes decision rule for minimum error, is proposed for kinship verification. Experimental results on two representative kinship data sets, namely the KinFaceW-I and the KinFaceW-II data sets, show the feasibility of the proposed method.
Identifier
84962920847 (Scopus)
ISBN
[9781479987764]
Publication Title
2015 IEEE 7th International Conference on Biometrics Theory Applications and Systems Btas 2015
External Full Text Location
https://doi.org/10.1109/BTAS.2015.7358768
Recommended Citation
Liu, Qingfeng; Puthenputhussery, Ajit; and Liu, Chengjun, "Inheritable Fisher vector feature for kinship verification" (2015). Faculty Publications. 6615.
https://digitalcommons.njit.edu/fac_pubs/6615
