Research on Facial Expression Capture Based on Two-Stage Neural Network

To generate realistic three-dimensional animation of virtual character,capturing real facial expression is the primary task.Due to diverse facial expressions and complex background,facial landmarks recognized by existing strategies have the problem of deviations and low accuracy.Therefore,a method for facial expression capture based on two-stage neural network is proposed in this paper which takes advantage of improved multi-task cascaded convolutional networks(MTCNN)and high-resolution network.Firstly,the convolution operation of traditional MTCNN is improved.The face information in the input image is quickly filtered by feature fusion in the first stage and Octave Convolution instead of the original ones is introduced into in the second stage to enhance the feature extraction ability of the network,which further rejects a large number of false candidates.The model outputs more accurate facial candidate windows for better landmarks recognition and locates the faces.Then the images cropped after face detection are input into high-resolution network.Multi-scale feature fusion is realized by parallel connection of multi-resolution streams,and rich high-resolution heatmaps of facial landmarks are obtained.Finally,the changes of facial landmarks recognized are tracked in real-time.The expression parameters are extracted and transmitted to Unity3D engine to drive the virtual character’s face,which can realize facial expression synchronous animation.Extensive experimental results obtained on the WFLW database demonstrate the superiority of the proposed method in terms of accuracy and robustness,especially for diverse expressions and complex background.The method can accurately capture facial expression and generate three-dimensional animation effects,making online entertainment and social interaction more immersive in shared virtual space.

Procedural modeling applied to the 3D city model of Bogota:A case study

Background Computer Generated Animations(CGA),when applied to three-dimensional(3D)city models(3DCM),can be used as powerful tools to support urban decision-making.This leads to a new paradigm,based on procedural modeling,that allows the integration of known urban structures.Methods This paper introduces a new workflow for the development of high-quality approximations of urban models in a short time and enables facilities to be imported from other cities into a given city model,following specific generation rules.Results Thus,this workflow provides a very simple approach to observe,study,and simulate the implementation of models already developed in other cities,in a city where they are not yet adopted.Examples of these models include all types of mobility systems and urban infrastructure.Conclusions This allows us to perceive the environmental impact of certain decisions in the real world,as well as to carry out simple simulations to determine the changes that can occur in the flows of people,traffic,and other city activities.