The invention belongs to the technical field of three-dimensional dynamic graph
processing, and particularly relates to a three-dimensional virtual character intelligent skinning method based on
deep learning, which particularly comprises the steps: skeleton generation (geometric contraction, edge folding and skeleton optimization) and skinning intelligent prediction (
feature extraction, model construction, model training and skinning prediction). According to the method, skeleton generation, binding and
skin weight assignment work can be automatically completed only through the grid model of the three-dimensional virtual character, so that a good effect can be achieved when the method is applied to grid models with different complexity degrees, skeleton binding and weight assignment are directly completed for the constructed three-dimensional virtual character, and the method is high in practicability and easy to popularize. When the method is applied to a high-precision three-dimensional model with a huge number of vertexes and patches, the manufacturing time of the skinned skeleton
animation can be greatly shortened, the cost can be reduced, the
animation manufacturing effect is vivid and natural, and the complexity of three-dimensional
animation manufacturing is simplified; and therefore, the method can be applied to the technical field of skinned skeleton animation manufacturing and is wide in prospect.