###
DOI:
Journal of Software:2018.29(S2):62-74

基于肌肉感知的手势交互模型
范俊君,田丰,黄进,刘杰,王宏安,戴国忠
(人机交互北京市重点实验室(中国科学院 软件研究所), 北京 100190;中国科学院大学 计算机与控制学院, 北京 100049)
Gesture Interaction Model Based on Muscle Sensing
FAN Jun-Jun,TIAN Feng,HUANG Jin,LIU Jie,WANG Hong-An,DAI Guo-Zhong
(Beijing Key Laboratory of Human-Computer Interaction(Institute of Software, The Chinese Academy of Sciences, Beijing 100190, China;School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing 100049, China)
Abstract
Chart / table
Reference
Similar Articles
Article :Browse 461   Download 526
Received:June 01, 2017    
> 中文摘要: 在人机交互技术由以计算机演化为以人为中心的背景下,通过感知肌肉活动的手势识别方法,因其可穿戴性、隐式交互性和可靠性的特点在近几年得到了人机交互研究领域的高度关注.但目前的相关研究缺乏统一的语义分析模型和系统模型支持研究和开发.为此,分析讨论了交互手势的分类并归纳总结出适合肌肉感知方法的输入原语,提出基于肌肉感知的手势交互语义分析模型和分层处理的系统结构模型,旨在提高该类型交互应用的研究和开发工作效率.最后分析了办公室环境下的操作手势交互应用场景,给出了该语义分析模型和分层系统结构模型的应用实例.
Abstract:Gesture interaction based on muscle sensing has received great attention due to its wearability, implicit interaction, and reliability under the background of human-computer interaction technique shifting from computer-centered to human-centered. However, current researchs lack of a unified semantic model and system model. This paper discussed the classification of interactive gestures, summarized the input primitives suitable for physiological computing technology, and proposed muscle sensing based gesture interaction semantic model and hierarchical processing a system model. Finally, this paper implemented a prototype of object operating gesture recognition under scenario of office environment.
文章编号:     中图分类号:    文献标志码:
基金项目:国家重点研发计划(2016YFB10011402);中国科学院前沿科学重点研究计划(QYZDY-SSW-JSC041) 国家重点研发计划(2016YFB10011402);中国科学院前沿科学重点研究计划(QYZDY-SSW-JSC041)
Foundation items:National Key Research and Development Plan (2016YFB10011402); Key Research Program of Frontier Sciences, CAS(QYZDY-SSW-JSC041)
Reference text:

范俊君,田丰,黄进,刘杰,王宏安,戴国忠.基于肌肉感知的手势交互模型.软件学报,2018,29(S2):62-74

FAN Jun-Jun,TIAN Feng,HUANG Jin,LIU Jie,WANG Hong-An,DAI Guo-Zhong.Gesture Interaction Model Based on Muscle Sensing.Journal of Software,2018,29(S2):62-74