Human skin color detection in RGB space with Bayesian estimation of beta mixture models
2010 (English)In: EUSIPCO 2010, EUROPEAN ASSOC SIGNAL SPEECH & IMAGE PROCESSING-EURASIP , 2010, 1204-1208 p.Conference paper (Refereed)
Human skin color detection plays an important role in the applicationsof skin segmentation, face recognition, and tracking. To builda robust human skin color classifier is an essential step. This paperpresents a classifier based on beta mixture models (BMM), whichuses the pixel values in RGB space as the features. We proposea Bayesian estimation method based on the variational inferenceframework to approximate the posterior distribution of the parametersin the BMM and take the posterior mean as a point estimateof the parameters. The well-known Compaq image database is usedto evaluate the performance of our BMM based classifier. Comparedto some other skin color detection methods, our BMM basedclassifier shows a better recognition performance.
Place, publisher, year, edition, pages
EUROPEAN ASSOC SIGNAL SPEECH & IMAGE PROCESSING-EURASIP , 2010. 1204-1208 p.
TRITA-S3-SIP, ISSN 1652-4500
Other Electrical Engineering, Electronic Engineering, Information Engineering Computer Science
Research subject SRA - ICT
IdentifiersURN: urn:nbn:se:kth:diva-34267ISI: 000349999100244ScopusID: 2-s2.0-84863807861OAI: oai:DiVA.org:kth-34267DiVA: diva2:420032
18th European Signal Processing Conference (EUSIPCO 2010). Aalborg, Denmark. August 23-27, 2010
QC 201111172011-05-302011-05-302015-12-07Bibliographically approved