A Corpus-Based and Complex Computing Digital Media System for 3D Animation

Abstract

In this paper, we design a corpus-based 3D animation digital media system to improve the accuracy of 3D animation generation and realize crossplatform animation display. The corpus module extracts high-precision data through web crawling, web cleaning, Chinese word separation, and text classification steps; the character animation generation module uses the semantic description method to expand the frame information description of the extracted data, calculates the object spatial 3D coordinates, and uses the built-in animation execution script to generate 3D character animation; the improved digital media player module uses the improved digital media player to realize crossplatform display of 3D character animations using the improved digital media player. By constructing multidimensional character relationships and combining multiple visualization methods, the complex and multifaceted social relationship network is made available to users in an intuitive and more acceptable and understandable mode. Through a large number of user surveys, it is proved that the visual analysis method combining real social and virtual social proposed in this paper provides a more adequate and reliable basis for friend recommendation and social network analysis; the combination of multiple character relationships with geographical information and the use of visualization to describe multidimensional historical character relationships provides a new research perspective for the research and exploration of humanistic neighborhoods. The experimental results prove that the designed system can effectively read known contents and extract keywords and generate 3D animation based on keyword features, with a high accuracy rate, fast response time, small frame loss rate, and crossplatform display animation advantages.