Accurate　and　robust　location　of　feature　point　is　a　difficult　and　challenging　issue　in　face　recognition.　In　this　paper　we　propose　a　new　approach　of　using　a　cascade　of　Multi-Resolution　Active　Shape　Models　(C-MR-ASM)　to　locate　facial　feature　points.　In　our　approach,　more　than　one　MR-ASMs　are　obtained　from　different　subsets　of　training　set　automatically,　and　these　MR-ASMs　are　integrated　in　a　cascade　to　locate　facial　feature　points.　Experimental　results　show　that　our　algorithm　is　more　accurate　than　traditional　MR-ASM.　The　contribution　of　this　paper　includes:　1,　unlike　traditional　MR-ASM,　the　training　set　is　divided　into　several　subsets　automatically　based　on　the　principle　a　trained　model　should　describe　all　the　samples　in　training　set　accurately.　2,　we　propose　the　new　cascade　framework,　which　integrates　all　the　subset　MR-ASM.　©　Springer-Verlag　Berlin　Heidelberg　2007.