]> BibSonomy publications for /bibtex/2d720a6acf4dbb0067004e7452c96c0cf/marcoalvarez http://www.bibsonomy.org/burst/bibtex/2d720a6acf4dbb0067004e7452c96c0cf/marcoalvarez BibSonomy BuRST Feed for /bibtex/2d720a6acf4dbb0067004e7452c96c0cf/marcoalvarez 2008-08-21T12:57:56+02:00 A comparison of pixel, edge and wavelet features for face detection using a semi-naive bayesian classifier http://www.bibsonomy.org/bibtex/2d720a6acf4dbb0067004e7452c96c0cf/marcoalvarez marcoalvarez 2008-05-14T11:33:59+02:00 Bayes ObjectDetection
A comparison of pixel, edge and wavelet features for face detection using a semi-naive bayesian classifier
J. Ross Beveridge and Jilmil Saraf and Ben Randall International Conference on Pattern Recognition 1175--1178 (2006)
to Bayes ObjectDetection on 2008-05-14 11:33:59 ]]> International Conference on Pattern Recognition1175--1178A comparison of pixel, edge and wavelet features for face detection using a semi-naive bayesian classifier2006Bayes ObjectDetection 2008-05-14 11:33:59.0Henry Schneiderman at Carnegie Mellon University developed a face detection algorithm based upon a semi-naive Bayesian classifier and 5/3 linear phase wavelets. This paper explores the relative value of these wavelet features compared to simpler pixel and edge features. Experiments suggest edge features are superior for highly controlled lighting, while pixel features are better and more stable for uncontrolled lighting. Tests use the Notre Dame face data collected in Fall 2003 and Spring 2004 and use over 400,000 face and non-face test image chips.