One class classification applied in facial image analysis

Vasileios Mygdalis, Alexandros Iosifidis, Anastasios Tefas, Ioannis Pitas

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

8 Citations (Scopus)
239 Downloads (Pure)

Abstract

In this paper, we apply One-Class Classification methods in facial image analysis problems. We consider the cases where the available training data information originates from one class, or one of the available classes is of high importance. We propose a novel extension of the One-Class Extreme Learning Machines algorithm aiming at minimizing both the training error and the data dispersion and consider solutions that generate decision functions in the ELM space, as well as in ELM
spaces of arbitrary dimensionality. We evaluate the performance in publicly available datasets. The proposed method compares favourably to other state-of-the-art choices.
Original languageEnglish
Title of host publication2016 IEEE International Conference on Image Process (ICIP 2016)
Subtitle of host publicationProceedings of a meeting held 25-29 September 2016, Phoenix, AZ, USA
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1644-1648
Number of pages5
ISBN (Electronic)9781467399616
ISBN (Print)9781467399623
DOIs
Publication statusPublished - Mar 2017
EventIEEE International Conference on Image Processing - Phoenix, Arizona, United States
Duration: 25 Sep 201628 Sep 2016

Publication series

NameProceedings of the IEEE International Conference on Image Processing (ICIP)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISSN (Print)2381-8549

Conference

ConferenceIEEE International Conference on Image Processing
Abbreviated titleICIP
CountryUnited States
CityPhoenix, Arizona
Period25/09/1628/09/16

Keywords

  • Facial image analysis
  • one-class classification
  • regularization

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