LAUSR

In this paper, an automatic method is proposed to generate a symmetry-aware kinematic skeleton for a human body model with an arbitrary pose and orientation. First, a template kinematic skeleton with semantics is embedded into the input human body model. Then, the joints of the embedded kinematic skeleton are refined according to the geometry of the human body model and some prior knowledge. Finally, a specific local coordinate system is defined on the kinematic skeleton and is used to distinguish the symmetry of the kinematic skeleton. In this way, the symmetric joints of the kinematic skeleton, e.g., the left knee joint and the right knee joint, can be distinguished. Quantitative and qualitative analysis and comparison show that the proposed method can generate a symmetry-aware kinematic skeleton with accurate joints and has no restrictions on the pose and orientation of the input human body model. Moreover, this paper presents validation of the proposed method in many applications, such as shape alignment, shape deformation, shape co-segmentation and shape correspondence.