SIFT flow based genetic fisher vector feature for kinship verification

Ajit Puthenputhussery, Qingfeng Liu, Chengjun Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

Anthropology studies show that genetic features are inherited by children from their parents resulting in visual resemblance between them. This paper presents a novel SIFT flow based genetic Fisher vector feature (SF-GFVF) which enhances the facial genetic features for kinship verification. The proposed SF-GFVF feature is derived by applying a novel similarity enhancement method based on SIFT flow and learning an inheritable transformation on the Fisher vector feature so as to enhance and encode the genetic features of parent and child image in kinship relations. In particular, the similarity enhancement method is first presented by applying the SIFT flow algorithm to the densely sampled SIFT features in order to intensify the genetic features. Further analysis shows the relation of the extracted genetic features to anthropological results and discovers interesting patterns in different kinship relations. Finally, an inheritable transformation is applied to the enhanced Fisher vector feature which is learned with the criterion of minimizing the distance between kinship samples and maximizing the distance between non-kinship samples. Experimental results on the two representative kinship databases, namely the KinFace W-I and the Kinship W-II data sets show that the proposed method is able to outperform other popular methods.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PublisherIEEE Computer Society
Pages2921-2925
Number of pages5
ISBN (Electronic)9781467399616
DOIs
StatePublished - Aug 3 2016
Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
Duration: Sep 25 2016Sep 28 2016

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2016-August
ISSN (Print)1522-4880

Other

Other23rd IEEE International Conference on Image Processing, ICIP 2016
CountryUnited States
CityPhoenix
Period9/25/169/28/16

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Keywords

  • Inheritable transformation
  • Kinship verification
  • SIFT flow based genetic Fisher vector feature

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