Considering Multisensor Data Fusion and Data-Driven Special Effects Animation Simulation

Abstract

The data-driven simulation algorithm uses the method of surface matching to establish the corresponding relationship between the surfaces of the two dynamic models at the same time. It also calculates the appropriate deformation field to align the animated character surface and then uses the interpolation operation to further expand the new animated character motion. With the promotion of industrial application requirements such as games, film and television, and education and entertainment, computer animation special effects simulation technology has a wide range of application prospects. Based on a multisensor and data-driven approach, this paper conducts a targeted study on the realistic simulation of typical special effects animations. Aiming at the high time complexity and time-consuming problems of simulation algorithms, data-driven simulation methods are studied and scenes or objects that simulate the real environment can be created. They are given different properties and parameters, and the desired results are obtained through computer calculation and rendering. Finally, it can be output into a smooth animation. Based on the animation simulation data and multisensor data fusion method proposed in this paper, the on-site calculation process can be accelerated and efficient animation simulation driven by data can be realized. In 3ds Max 2013, there is also a small function that can sort the bone list in ascending or descending order in alphabetical and numerical order. This helps manage bones attached to the skin modifier more efficiently. This saves a lot of time when picking bones. About 44.3% of the people during the study were proficient in the use of software. After 1200 frames, the number of foam particles increases sharply, and the two-way coupling algorithm takes time. As the number of foam particles decreases, the time required for bidirectional coupling decreases. The article gives a brief description of the data-driven fusion model. The fluid simulation algorithm generates two different sequences by utilizing two different sets of setup parameters. It is then transformed into a spatiotemporal surface as input data for the fusion model. This research contributes to the development of special effects animation simulations.