This　paper　proposes　a　novel　method　for　automatic　extraction　of　human　body　skeletons　from　3D　dynamic　shapes　by　taking　advantage　of　geometry　properties　of　static　shapes,　knowledge　of　anthropometry　(priori　knowledge　of　human　body　anatomy),　and　kinematics　characteristics　of　dynamic　shapes.　The　method　consists　of　three　steps.　In　Step　I,　the　human　body　is　divided　into　five　parts　including　four　limbs　and　the　torso　based　on　the　Reeb　graph　created　by　a　Morse　function,　which　is　defined　on　the　surface　mesh　of　a　reference　pose　as　geodesic　distanee.　Then,　limbs　and　torso　are　sub-segmented　using　statistical　anthropometric　proportions.　In　Step　II,　seed　points　that　exhibit　the　best　rigid　transformation　are　identified　in　the　middle　parts　of　the　sub-segments　by　the　mesh　edge-length　deviation　induced　by　its　transformation　through　time.　In　Step　III,　we　use　these　seed　points　to　determine　joint　locations　of　the　skeleton.　An　empirical　experiment　demonstrates　that　the　proposed　method　is　able　to　extract　skeletons　from　3D　dynamic　meshes　automatically.　The　accuracy　of　the　proposed　method　appears　to　be　supelior　to　that　of　the　existing　methods.　©　2011　by　Taylor　&　Francis　Group,　LLC.