Automatic Facial Recognition: A Systematic Review on the Problem of Light Variation

  • Kelvin S. Prado
  • Norton T. Roman
  • Valdinei F. Silva
  • João L. BernardesJr.
  • Luciano A. Digiampietri
  • Enrique M. Ortega
  • Clodoaldo A. M. Lima
  • Luis M. V. Cura
  • Marcelo M. Antunes
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9732)

Abstract

In this systematic review we approach the problem of light variation in tasks related to automatic facial recognition, a feature that can significantly affect the performance of automatic systems. We then carry out a broad research on the state of the art, describing and comparing current research in this subject. The review relies on a set of processes for searching, analysing and describing research that is considered relevant to this work, and which are reported in more detail in this article. In analysing the results, we could notice that the problem of light variation is still one of the greatest challenges in the area of facial recognition, which translates in a good deal of research directly tackling this problem, trying to solve it or, at least, mitigate it somehow, so as to improve the performance of facial recognition techniques and algorithms. Finally, results also show that this is a problem of great concern by researchers in the field, insomuch that even those articles that do not directly deal with it still make explicit the researchers’ concern about it.

Keywords

Facial Recognition Local Binary Pattern Thermal Image Face Detection Light Variation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Kelvin S. Prado
    • 1
  • Norton T. Roman
    • 1
  • Valdinei F. Silva
    • 1
  • João L. BernardesJr.
    • 1
  • Luciano A. Digiampietri
    • 1
  • Enrique M. Ortega
    • 2
  • Clodoaldo A. M. Lima
    • 1
  • Luis M. V. Cura
    • 3
  • Marcelo M. Antunes
    • 2
  1. 1.University of São PauloSão PauloBrazil
  2. 2.Central Kung-Fu AcademyCampinasBrazil
  3. 3.Campo Limpo Paulista FacultyCampo Limpo PaulistaBrazil

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