3D Modeling Method Based on Deep Belief Networks (DBNs) and Interactive Evolutionary Algorithm (IEA)

3D modeling usually refers to be the use of 3D software to build production through the virtual 3D space model with 3D data. At present, most 3D modeling software such as 3dmax, FLAC3D and Midas all need adjust models to get a satisfactory model or by coding a precise modeling. There are many matters such as complicated steps, strong profession, the high modeling cost. Aiming at this problem, the paper presents a new 3D modeling methods which is based on Deep Belief Networks (DBN) and Interactive Evolutionary Algorithm (IEA). Following this method, firstly, extract characteristic vectors from vertex, normal, surfaces of the imported model samples. Secondly, use the evolution strategy, to extract feature vector for stochastic evolution by artificial grading control the direction of evolution, and in the process to extract the characteristics of user preferences. Then, use evolution function matrix to establish the fitness approximation evaluation model, and simulate subjective evaluation. Lastly, the user can control the whole machine simulation evaluation process at any time, and get a satisfactory model. The experimental results show that the method in this paper is feasible.