A single layer feedforward fusion network for face verification

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

doi:10.1109/ICARCV.2014.7064432

A single layer feedforward fusion network for face verification

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

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	944-948
Number of pages	5
ISBN (Electronic)	9781479951994
DOIs	https://doi.org/10.1109/ICARCV.2014.7064432
Publication status	Published - 2014 Jan 1
Event	2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014 - Singapore, Singapore Duration: 2014 Dec 10 → 2014 Dec 12

Publication series

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

Other

Other	2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014
Country	Singapore
City	Singapore
Period	14/12/10 → 14/12/12

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All Science Journal Classification (ASJC) codes

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

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

Oh, Beom Seok ; Oh, Kangrok ; Toh, Kar Ann ; Beng Jin Teoh, Andrew. / A single layer feedforward fusion network for face verification. 2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 944-948 (2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014).

@inproceedings{72250234721a4c2c88b72f2aa80bc9ff,

title = "A single layer feedforward fusion network for face verification",

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.",

author = "Oh, {Beom Seok} and Kangrok Oh and Toh, {Kar Ann} and {Beng Jin Teoh}, Andrew",

year = "2014",

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booktitle = "2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014",

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note = "2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014 ; Conference date: 10-12-2014 Through 12-12-2014",

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Oh, BS, Oh, K, Toh, KA & 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., 7064432, 2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014, Institute of Electrical and Electronics Engineers Inc., pp. 944-948, 2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014, Singapore, Singapore, 14/12/10. https://doi.org/10.1109/ICARCV.2014.7064432

A single layer feedforward fusion network for face verification. / Oh, Beom Seok; Oh, Kangrok; Toh, Kar Ann ; Beng Jin Teoh, Andrew.

2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 944-948 7064432 (2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - 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.

AB - 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.

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

Access to Document

10.1109/ICARCV.2014.7064432