Paper
17 December 1998 Gaussian mixture model for human skin color and its applications in image and video databases
Ming-Hsuan Yang, Narendra Ahuja
Author Affiliations +
Abstract
This paper is concerned with estimating a probability density function of human skin color, using a finite Gaussian mixture model, whose parameters are estimated through the EM algorithm. Hawkins' statistical test on the normality and homoscedasticity (common covariance matrix) of the estimated Gaussian mixture models is performed and McLachlan's bootstrap method is used to test the number of components in a mixture. Experimental results show that the estimated Gaussian mixture model fits skin images from a large database. Applications of the estimated density function in image and video databases are presented.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ming-Hsuan Yang and Narendra Ahuja "Gaussian mixture model for human skin color and its applications in image and video databases", Proc. SPIE 3656, Storage and Retrieval for Image and Video Databases VII, (17 December 1998); https://doi.org/10.1117/12.333865
Lens.org Logo
CITATIONS
Cited by 274 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Skin

RGB color model

Expectation maximization algorithms

Statistical analysis

Data modeling

Databases

Statistical modeling

RELATED CONTENT

What impacts skin color in digital photos?
Proceedings of SPIE (February 03 2014)
Face detection and recognition in a video sequence
Proceedings of SPIE (August 25 2004)
Automatic model-based anchorperson detection
Proceedings of SPIE (January 01 2001)

Back to Top