Nonlinear dynamic analysis of mid-air gesture recognition

被引：0
|
作者：
Feng G. [1 ,3 ]
Hou W. [2 ,3 ]
Zhou H. [2 ,3 ]
You Z. [2 ,3 ]
机构：
[1] School of Automation, Beijing University of Posts and Telecommunications, Beijing
[2] School of Digital Media and Design Arts, Beijing University of Posts and Telecommunications, Beijing
[3] Beijing Key Laboratory of Network Systems and Network Culture, Beijing University of Posts and Telecommunications, Beijing
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2020年 / 26卷 / 08期
关键词：
Chaotic dynamics; Feature engineering; Gesture recognition; Virtual reality interaction;
D O I：
10.13196/j.cims.2020.08.012
中图分类号：
学科分类号：
摘要：
For the problem that the performance of conventional continuous gestures recognition was mainly affected by factors such as variations in the movement duration and inaccurate feature extraction, the nonlinear dynamic model of chaos theory was used to explore the inherent chaotic motion characteristics of volley dynamic gestures, and a fuzzy interactive framework based on chaotic dynamic characteristics was established. Leapmotion head-mounted display was embedded with discrete observation to obtain finger tracks. Assuming that a particular type of chaotic dynamical system might simulate the gesture motion model, the feature matrix composed with chaotic feature factors was established based on Phase Space Reconstruction (PSR) for identifying classification. The hypothesis was evaluated with a database of alphabetic gestures, and an accuracy of 96.6% in the experiment was achieved. © 2020, Editorial Department of CIMS. All right reserved.
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页码：2116 / 2123
页数：7
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