A single layer feedforward fusion network for face verification

Beom Seok Oh, Kangrok Oh, Kar Ann Toh, Andrew Beng Jin Teoh

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

1 Citation (Scopus)

Abstract

In this paper, a single hidden-layer feedforward fusion network is proposed for face identity verification. Essentially, the feature extraction, matching score calculation and fusion algorithm design steps are integrated and absorbed into a hidden layer of the model. Each hidden node works on the raw face image directly and produces an Euclidean distance based match score within the network. These scores are then incorporated with output weights to produce a fused score at the final stage. Our experimental study conducted using three face databases shows that the proposed model consistently outperforms competing methods.

Original languageEnglish
Title of host publication2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages944-948
Number of pages5
ISBN (Electronic)9781479951994
DOIs
Publication statusPublished - 2014
Event2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014 - Singapore, Singapore
Duration: 2014 Dec 102014 Dec 12

Publication series

Name2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014

Other

Other2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014
CountrySingapore
CitySingapore
Period14/12/1014/12/12

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Artificial Intelligence
  • Control and Systems Engineering

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  • Cite this

    Oh, B. S., Oh, K., Toh, K. A., & Beng Jin Teoh, A. (2014). A single layer feedforward fusion network for face verification. In 2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014 (pp. 944-948). [7064432] (2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICARCV.2014.7064432