This　paper　presents　a　novel　matching　method　based　on　particle　swarm　optimization　(PSO)　algorithm　for　3D　face　reconstruction.　The　new　model-matching　algorithm　can　make　the　reconstruction　has　faster　convergent　speed　and　better　result　than　before.　Having　constructed　the　morphable　model,　PSO　algorithm　is　proposed　to　tackle　model　matching　problem.　PSO　algorithm　is　a　swarm　intelligence-based　optimization　algorithm　which　is　independent　of　initial　values　and　the　gradient　information　of　object　function.　In　the　course　of　optimization　each　individual　has　their　own　memory　about　the　optimal　position　they　have　arrived　and　the　information　among　individuals　can　be　exchange　with　each　other.　This　will　be　great　helpful　to　improve　precision　and　convergence　speed　of　the　algorithm.　The　Experimental　results　show　that　the　proposed　matching　method　has　good　performance　on　3D　face　reconstruction.　©　2009　Binary　Information　Press.