The　performance　of　human　face　recognition　algorithms　is　seriously　affected　by　two　important　factors:　head　pose　and　lighting　condition.　The　effective　processing　of　the　pose　and　illumination　variations　is　a　vital　key　for　improving　the　recognition　rate.　This　paper　proposes　a　novel　method　that　can　synthesize　images　with　different　head　poses　and　lighting　conditions　by　using　a　modified　3D　CANDIDE　model,　linear　vertex　interpolation　and　NURBS　curve　surface　fitting　method,　as　well　as　a　mixed　illumination　model.　A　specific　Eigenface　method　is　also　proposed　to　perform　face　recognition　based　on　a　pre-estimated　head　pose　method.　Experimental　results　show　that　the　quality　of　the　synthesized　images　and　the　recognition　performance　are　good.　©　Springer-Verlag　Berlin　Heidelberg　2005.