Random sparse representation for thermal to visible face recognition

Samira Reihanian, Ehsan Arbabi, Behrouz Maham

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

1 Citation (Scopus)

Abstract

Heterogeneous face recognition (HFR) has a prominent importance in sophisticated face recognition systems. Thermal to visible scenario, where the gallery and the probe images are respectively captured in visible and long wavelength infrared (LWIR) band, is one of the most challenging and interesting HFR scenarios. Since the formation of thermal images does not require an external illumination source, the deployment of thermal probe images is practical even in totally darkness conditions such as night security surveillance systems. In this paper, we propose an ensemble classifier which uses the random subspace idea for defining different representations of each image in distinct base learners, and exploits the sparse representation algorithm for the classification of thermal probe images. According to the experimental results, our proposed algorithm leads significant performance improvements in the area of thermal to visible face recognition and achieves the average Rank-1 accuracy of 89.33 percent.

Original languageEnglish
Title of host publication2017 IEEE Symposium on Computers and Communications, ISCC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1380-1385
Number of pages6
ISBN (Electronic)9781538616291
DOIs
Publication statusPublished - Sep 1 2017
Event2017 IEEE Symposium on Computers and Communications, ISCC 2017 - Heraklion, Greece
Duration: Jul 3 2017Jul 7 2017

Conference

Conference2017 IEEE Symposium on Computers and Communications, ISCC 2017
CountryGreece
CityHeraklion
Period7/3/177/7/17

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Mathematics(all)
  • Computer Science Applications
  • Computer Networks and Communications

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  • Cite this

    Reihanian, S., Arbabi, E., & Maham, B. (2017). Random sparse representation for thermal to visible face recognition. In 2017 IEEE Symposium on Computers and Communications, ISCC 2017 (pp. 1380-1385). [8024716] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCC.2017.8024716