In　this　paper,　we　present　a　novel　3D　face　recognition　algorithm　based　on　the　sparse　representation.　First,　a　3D　face　normalization　approach　is　proposed　to　deal　with　the　raw　faces.　Then,　three　types　of　facial　geometrical　features　are　extracted　to　describe　the　3D　faces.　Meanwhile,　in　order　to　guarantee　the　feasibility　of　the　sparse　representation　framework　and　promote　the　recognition　efficiency,　a　novel　feature　ranking　scheme　based　on　Fisher　linear　discriminant　analysis　(FLDA)　is　designed　to　arrange　the　facial　descriptors.　Finally,　the　sparse　representation　framework　is　used　to　collect　all　the　face　features,　and　it　addresses　the　recognition　task.　The　experiments　tested　on　the　BJUT-3D　and　FRGC　v2.0　databases　demonstrate　the　validity　of　the　proposed　3D　face　recognition　algorithm,　and　the　necessity　of　the　FLDA　ranking　scheme　in　the　sparse　representation　framework.