Research on Virtual Interactive Animation Design System Based on Deep Learning

Abstract

With the rapid development of computer network technology, the advantages of virtual reality technology in the field of instant messaging are becoming more and more significant. Virtual reality technology plays an important role in communication networks, including enhanced resource utilization, device redundancy, immersion, interactivity, conceptualization, and holography. In this paper, we use the basic theory of Restricted Boltzmann Machine to establish a semisupervised spatio-temporal feature model through the animation capture data style recognition problem. The bottom layer can be pretrained with a large amount of unlabeled data to enhance the model’s feature perception capability of animation data, and then train the high-level supervised model with the labeled data to finally obtain the model parameters that can be used for the recognition task. The layer-by-layer training method makes the model have good parallelism, that is, when the layer-by-layer training method makes the model well parallelized, that is, when the bottom features cannot effectively represent the animation features, such as overfitting or underfitting, only the bottom model needs to be retrained, while the top model parameters can be kept unchanged. Simulation experiments show that the design assistance time of this paper’s scheme for animation is reduced by 10 minutes compared to baseline.

Virtual Reality Animation Interaction Design using Bayesian Physics-Informed Neural Network with Archimedes Optimization Algorithm Based Scene Modelling

“…The proposed VRAID-BPINN-AOA method is implemented in MATLAB and evaluated under some metrics. Obtained results of HAD-TSV-ITF-CZNN technique are analysed with existing techniques likes VI-AD-RBM [21],GDL-VALD-GAN [22], HID-LVIR-CNN [23]correspondingly.…”

“…Liu [21] have presented Studying Design Systems for Virtual Interactive Animation with a Foundation in Deep Learning Using the problem of style recognition in animation capture data, the fundamentals of the Restricted Boltzmann Machine are applied to create a semi-supervised spatio-temporal feature model. When the top model's parameters remain unchanged and only the bottom model requires retraining, the model is considered well parallelized.…”

Retracted: Research on Virtual Interactive Animation Design System Based on Deep Learning

“…Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [ 1 ]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process: Discrepancies in scope Discrepancies in the description of the research reported Discrepancies between the availability of data and the research described Inappropriate citations Incoherent, meaningless and/or irrelevant content included in the article Peer-review manipulation …”