We present an efficient polygonization approach for tree trunks modeled by line skeleton-based convolution surfaces.A quad-dominated non-convex bounding polyhedron is firstly created along the skeleton,which is then tetrahedralized and subdivided into the pre-defined resolution.After that,the iso-surface within each tetrahedron is extracted using marching tetrahedra.Our algorithm can generate polygons with adaptive edge lengths according to the thickness of the trunk.In addition,we present an efficient CUDA-based parallel algorithm utilizing the high parallelism of the tetrahedron subdivision,the potential field calculation,and the iso-surface extraction.