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Reconstruction of Human Faces from Its Eigenfaces
ECE Department, Mallabhum Institute of Technology, West Bengal, India.
CSE Department, Mallabhum Institute of Technology, West Bengal, India.
2014 (English)In: International Journal of Advanced Research In Computer Science and Software Engineering, ISSN 2277-6451, E-ISSN 2277-128X, Vol. 4, no 1, p. 209-215Article in journal (Refereed) Published
Abstract [en]

Eigenface or Principal Components Analysis (PCA) methods have demonstrated their success in face recognition, detection and tracking. In this paper we have used this concept to reconstruct or represent a face as a linear combination of a set of basis images. The basis images are nothing but the eigenfaces. The idea is similar to represent a signal in the form of a linear combination of complex sinusoids called the Fourier Series. The main advantage is that the number of eigenfaces required is less than the number of face images in the database. Selection of number of eigefaces is important here. Here we investigate what is the number of minimum eigenface that is required for faithful production of a face image.

Place, publisher, year, edition, pages
Advanced Research International Publication House , 2014. Vol. 4, no 1, p. 209-215
Keywords [en]
Face reconstruction, Eigen faces, Eigen vectors, Principal component analysis (PCA), Fourier Series
National Category
Engineering and Technology Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:oru:diva-80539OAI: oai:DiVA.org:oru-80539DiVA, id: diva2:1413368
Available from: 2020-03-10 Created: 2020-03-10 Last updated: 2020-03-10

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Chakraborty, Subham

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
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Output format
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