Converting near infrared facial images to visible light images using skin pigment model

Kimshing Goh, Tetsu Matsukawa, Takahiro Okabe, Yoichi Sato

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

2 Citations (Scopus)

Abstract

In this paper, we propose a physics-based method to synthesize facial images in visible wavelengths from multi-band near infrared (NIR) images. The study on photometric properties of human skin shows that melanin and hemoglobin components are dominant factors that affect the skin appearance under different light spectrum. Specifically, a set of intensities observed at a certain surface point with varying wavelength is represented by a linear combination of both the pigment components. Our proposed method learns the spectral basis vectors, which describe absorbance due to both the pigments, from multispectral image dataset by using Independent Component Analysis (ICA). Then, our method estimates the coefficients, which are pixel-wise densities of both the pigments, from a multiband NIR image, and finally converts it to a visible light (VIS) image. We demonstrate that our proposed method works well for real facial images even though only a small dataset is available for learning basis vectors.

Original languageEnglish
Title of host publicationProceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013
PublisherMVA Organization
Pages153-156
Number of pages4
ISBN (Print)9784901122139
Publication statusPublished - 2013
Externally publishedYes
Event13th IAPR International Conference on Machine Vision Applications, MVA 2013 - Kyoto, Japan
Duration: May 20 2013May 23 2013

Publication series

NameProceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013

Conference

Conference13th IAPR International Conference on Machine Vision Applications, MVA 2013
CountryJapan
CityKyoto
Period5/20/135/23/13

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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