research-article

Discrete area filters in accurate detection of faces and facial features

Author:

Jacek NaruniecAuthors Info & Claims

Image and Vision Computing, Volume 32, Issue 12

Pages 979 - 993

https://doi.org/10.1016/j.imavis.2014.09.004

Published: 01 December 2014 Publication History

Abstract

This paper introduces a new method for detection of faces and facial features. Proposed algorithm denies the thesis that bottom-up solutions can't work at reasonable speed. It introduces fast detection - about 9 frames per second for a 384í 256 image - while preserving accurate details of the detection. Main experiments focus on the detection of the eye centers - crucial in many computer vision systems such as face recognition, eye movement detection or iris recognition, however algorithm is tuned to detect 15 fiducial face points. Models were trained on nearly frontal faces. Bottom-up approach allows to detect objects under partial occlusion - particularly two out of four face parts (left eye, right eye, nose, mouth) must be localized. Precision of the trained model is verified on the Feret dataset. Robustness of the face detection is evaluated on the BioID, LFPW, Feret, GT, Valid and Helen databases in comparison to the state of the art detectors.

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Cited By

Wrobel KDoroz RPorwik PNaruniec JKowalski M(2017)Using a Probabilistic Neural Network for lip-based biometric verificationEngineering Applications of Artificial Intelligence10.1016/j.engappai.2017.06.00364:C(112-127)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1016/j.engappai.2017.06.003

Discrete area filters in accurate detection of faces and facial features
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
      2. Computer vision tasks
  2. Machine learning

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cover image Image and Vision Computing

Image and Vision Computing Volume 32, Issue 12

December 2014

238 pages

ISSN:0262-8856

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Copyright © Elsevier B.V.

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Butterworth-Heinemann

United States

Publication History

Published: 01 December 2014

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Cited By

Wrobel KDoroz RPorwik PNaruniec JKowalski M(2017)Using a Probabilistic Neural Network for lip-based biometric verificationEngineering Applications of Artificial Intelligence10.1016/j.engappai.2017.06.00364:C(112-127)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1016/j.engappai.2017.06.003

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