TOWARDS AN AUTOMATIC HUMAN FACE LOCALIZATION SYSTEM
Kin Choong Yow and Roberto Cipolla
July 1995
This paper describes a method to detect and locate human faces in an image given no prior information about the size, orientation, and viewpoint of the faces in the image. This method uses a family of Gaussian derivative filters to search and extract human facial features from the image and then group them together into a set of partial faces using their geometric relationship. A belief network is then constructed for each possible face candidate and the belief values updated by evidences propagating through the network. Different instances of detected faces are then compared using their belief values and improbable face candidates discarded. The algorithm is tested on different instances of faces with varying sizes, orientation and viewpoint and the results indicate a 91% success rate in detection under viewpoint variation.
If you have difficulty viewing files that end '.gz'
,
which are gzip compressed, then you may be able to find
tools to uncompress them at the gzip
web site.
If you have difficulty viewing files that are in PostScript, (ending
'.ps'
or '.ps.gz'
), then you may be able to
find tools to view them at
the gsview
web site.
We have attempted to provide automatically generated PDF copies of documents for which only PostScript versions have previously been available. These are clearly marked in the database - due to the nature of the automatic conversion process, they are likely to be badly aliased when viewed at default resolution on screen by acroread.