Personal tools
You are here: Home → Knowledge Base → Statistical Classification of Skin Color Pixels from MPEG Videos  

Statistical Classification of Skin Color Pixels from MPEG Videos

Main information
Detection and classification of skin regions plays important roles in many image processing and vision applications. In this paper, we present a statistical approach for fast skin detection in MPEG-compressed videos. Firstly, conditional probabilities of skin and non-skin are extracted from manual marked training images. Then, candidate skin pixels are identified using the Bayesian maximum a posteriori decision rule. An optimal threshold is then obtained by analysis of probability error on the basis of the likelihood ratio histogram of skin and nonskin pixels. Experiments from sequences with varying illuminations have demonstrated that effectiveness of our approach. 
No referenced Knowhow defined
WP5: Detection, Extraction and Annotation of Knowledge. 
School of Informatics University of Bradford  Jianmin Jiang, Jinchang Ren 
2008-01-24 17:12  Request for more detail


Access and Use Rights
For LIVE project internal research purposes only.  For LIVE project internal development purposes only. 


Protection Status
Copyright School of Informatics, University of Bradford.  Add to LIVE's Intellectual Property Watch List 
Add to LIVE's Intellectual Property Watch List  Add to LIVE's Intellectual Property Watch List 
 
ACIVS 2007: 395-405 
Closed, attachment is not public 


This item is not available for public download. For further information click on Request for more details above

LIVE's knowledge base
  • What is available here?

Here you can search and access the documented work of the LIVE project. Documents include the official reporting of the project's work known as "deliverables", scientific and technical publications, study reports, press material, presentation material  as well as IPR pending material.

  • How can I access the material?

You can search this knowledge base by project partner, work area or key words.

By simply clicking "all" the complete list of documents will be listed.

  • Is everything open to the public?

Please note that only those publications marked in green have been cleared for immediate public access. To request access to those publications not open please click on the "request for more detail" link in the relevant document. Your request will be automatically sent to the authors for consideration.