<XML><RECORDS><RECORD><REFERENCE_TYPE>3</REFERENCE_TYPE><REFNUM>7760</REFNUM><AUTHORS><AUTHOR>Balasuriya,L.S.</AUTHOR><AUTHOR>Kodikara,N.D.</AUTHOR></AUTHORS><YEAR>2000</YEAR><TITLE>Frontal View Human Face Detection and Recognition</TITLE><PLACE_PUBLISHED>Second International Information Technology Conference, Colombo </PLACE_PUBLISHED><PUBLISHER>N/A</PUBLISHER><LABEL>Balasuriya:2000:7760</LABEL><KEYWORDS><KEYWORD>Face recognition</KEYWORD></KEYWORDS<ABSTRACT>This paper is about an attempt to unravel the classical problem of automated human face recognition. A near realtime, fully automated computer vision system was developed to detect and recognise expressionless, frontalview human faces in static images. In the implemented system, automated face detection was achieved using a deformable template algorithm based on image invariants. The natural symmetry of human faces was utilised to improve the efficiency of the face detection model. The deformable template was run down the line of symmetry of the face in search of the exact face location. Once the location of the face in an image was known, this pixel region was extracted and the test subject was recognized using principal component analysis, also known as the eigenface approach. </ABSTRACT></RECORD></RECORDS></XML>