增强用户体验下的集成人机交互仿真  

Integrated Human-Computer Interaction Simulation under Enhanced User Experience

作　　者：张艾佳 刘正捷[1] ZHANG Ai-jia;LIU Zheng-jie(School of Information Science and Technology,Dalian Maritime University,Dalian Liaoning 116026,China)

机构地区：[1]大连海事大学信息科学技术学院,辽宁大连116026

出　　处：《计算机仿真》2023年第4期476-479,498,共5页Computer Simulation

摘　　要：采用目前方法在虚拟现实技术中进行人机交互时,没有构建数据传输模型,难以获取人机交互过程中产生的数据和信息,存在主机接收数据概率低、特征识别率低、特征识别准确率低和用户满意度低的问题。提出增强用户体验下的集成人机交互方法,在博弈论的基础上构建数据传输模型,将其应用在人机交互过程中,采集人机交互产生的相关数据和信息,根据采集的数据获取用户的需求,增强用户体验,提高用户的满意度。通过非负矩阵分解提取数据传输模型采集数据的特征,并将提取的特征输入分类器中进行特征识别,实现人机交互。实验结果表明,所提方法的主机接收数据概率高、特征识别率高、特征识别准确率高、用户满意度高。When using the current method to conduct human-computer interaction in virtual reality technology,it is difficult to obtain the data and information generated in the human-computer interaction process without building a data transmission model.There are problems such as low probability of host receiving data,low rate of feature recognition,low rate of feature recognition accuracy and low user satisfaction.Therefor,an integrated human-computer interaction method based on enhanced user experience was presented in the paper.Based on game theory,the data transmission model was built and applied in the process of human-computer interaction.Relevant data and information generated by human-computer interaction were collected.According to the collection results,the needs of users were obtained in order to enhance the user experience and improve user satisfaction.According to the nonnegative matrix,the data transmission model was decomposed to extract the features to collect data and input into the classifier to identify the features,realizing human-computer interaction.The experimental results show that this method has high data receiving probability,feature recognition rate,feature recognition accuracy and user satisfaction.

关 键 词：用户体验 虚拟现实技术 人机交互 数据传输模型 非负矩阵分解 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]