In　this　paper,　we　use　local　linear　embedding　and　linear　discriminant　analysis　for　face　recognition.　Local　linear　embedding　method　is　used　to　nonlinearly　map　high-dimensional　face　images　to　low-dimensional　feature　space.　To　recover　space　structure　of　face　images,　we　use　3D　morphable　model　to　derive　multiple　images　of　a　person　from　one　single　image.　Experimental　results　on　ORL　and　UMIST　face　database　show　that　our　method　make　impressive　performance　improvement　compared　with　conventional　Fisherface　method.