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Implementation of Face Detection Using OpenCV for Internet Dressing Room

  • Li-Der Chou
  • Chien-Cheng Chen
  • Chun-Kai Kui
  • Der-Ching Chang
  • Tai-Yu Hsu
  • Bing-Ling Li
  • Yi-Ching Lee
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 260)

Abstract

Human face detection is an important technology that is positively developed by industry. Therefore, this paper proposes a dressing application that adopts a face detection technology for better human life. Furthermore, this paper detects human face by using the combination of OpenCV and Internet camera. When the proposed application detect a human face, the proposed application dresses target on a screen, such as putting one selected cloth on the correspond position of human. Finally, the proposed application has a dressing ability for customers who are shopping clothes on Internet, and the dressing ability improves the sales performance of Internet store.

Keywords

OpenCV Internet camera Face detection 

References

  1. 1.
    Intel Corporation, Open source computer vision library. Reference manual, Copyright © 1999–2001. Available. http://software.intel.com/en-us
  2. 2.
  3. 3.
    Wren C, Azarbayejani A, Darrell T, Pentland A (1997) Pfinder: real-time tracking of the human body. IEEE Trans Pattern Anal Mach Intell 19(7):780–785CrossRefGoogle Scholar
  4. 4.
    Lorsakul A, Suthakorn J Traffic sign recognition for intelligent vehicle/driver assistance system using neural network on OpenCV. International conference on ubiquitous robots and ambient intelligenceGoogle Scholar
  5. 5.
    Haj MAI, Amato A, Roca X, Gonzàlez J (2007) Face detection in color images using primitive shape features. Computer Recognition Systems 2, vol 45Google Scholar
  6. 6.
    Haj MA et al (2009) Robust and efficient multipose face detection using skin color segmentation. Proceedings of the 4th Iberian conference on pattern recognition and image analysisGoogle Scholar
  7. 7.
    Chen L-F, Liao H-YM, Lin J-C, Han C–C (2001) Why recognition in a statistics-based face recognition system should be based on the pure face portion: a probabilistic decision-based proof. Pattern Recogn 34(5):1393–1403CrossRefMATHGoogle Scholar
  8. 8.
    Lapedriza A, Marin-Jimenez MJ, Vitria J (2006) Gender recognition in non-controlled environment. 18th IEEE international conference on pattern recognition, vol 3, pp 834–837Google Scholar
  9. 9.
    Hu M (1962) Visual pattern recognition by moment invariants. IRE Trans Inf Theory IT-8 179–187Google Scholar
  10. 10.
    Teague MR (1980) Image analysis via the general theory of moments. J Opt Soc Am 70:920–930MathSciNetCrossRefGoogle Scholar
  11. 11.
    Khotanzad A, Hong YH (1990) Invariant image recognition by Zernike moments. IEEE Trans Pattern Anal Mach Intell 489–497Google Scholar
  12. 12.
    Ahonen T, Hadid A, Pietikäinen M (2004) Face recognition with local binary patterns. ECCV 2004Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Li-Der Chou
    • 1
  • Chien-Cheng Chen
    • 1
  • Chun-Kai Kui
    • 1
  • Der-Ching Chang
    • 1
  • Tai-Yu Hsu
    • 1
  • Bing-Ling Li
    • 1
  • Yi-Ching Lee
    • 1
  1. 1.Department of Computer Science and Information EngineeringNational Central UniversityJhongliTaiwan

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