An interactive VR system based on full-body tracking and gesture recognition

被引:0
|
作者
Zeng, Xia [1 ]
Sang, Xinzhu [1 ]
Chen, Duo [1 ]
Wang, Peng [1 ]
Guo, Nan [1 ]
Yan, Binbin [1 ]
Wang, Kuiru [1 ]
机构
[1] Beijing Univ Posts & Telecommun, State Key Lab Informat Photon & Opt Commun, POB 72, Beijing 100876, Peoples R China
来源
基金
美国国家科学基金会;
关键词
virtual reality; human-centered interaction; full-body tracking; gesture recognition; Microsoft Kinect; Unity3D; natural user interface; walking-in place;
D O I
10.1117/12.2247808
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Most current virtual reality (VR) interactions are realized with the hand-held input device which leads to a low degree of presence. There is other solutions using sensors like Leap Motion to recognize the gestures of users in order to interact in a more natural way, but the navigation in these systems is still a problem, because they fail to map the actual walking to virtual walking only with a partial body of the user represented in the synthetic environment. Therefore, we propose a system in which users can walk around in the virtual environment as a humanoid model, selecting menu items and manipulating with the virtual objects using natural hand gestures. With a Kinect depth camera, the system tracks the joints of the user, mapping them to a full virtual body which follows the move of the tracked user. The movements of the feet can be detected to determine whether the user is in walking state, so that the walking of model in the virtual world can be activated and stopped by means of animation control in Unity engine. This method frees the hands of users comparing to traditional navigation way using hand-held device. We use the point cloud data getting from Kinect depth camera to recognize the gestures of users, such as swiping, pressing and manipulating virtual objects. Combining the full body tracking and gestures recognition using Kinect, we achieve our interactive VR system in Unity engine with a high degree of presence.
引用
收藏
页数:7
相关论文
共 50 条
  • [11] A Framework for Immersive VR and Full-Body Avatar Interaction
    Camporesi, Carlo
    Kallmann, Marcelo
    2013 IEEE VIRTUAL REALITY CONFERENCE (VR), 2013, : 79 - 80
  • [12] Full-body Gesture Recognition Using Inertial Sensors for Playful Interaction with Small Humanoid Robot
    Cooney, Martin D.
    Becker-Asano, Christian
    Kanda, Takayuki
    Alissandrakis, Aris
    Ishiguro, Hiroshi
    IEEE/RSJ 2010 INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2010), 2010,
  • [13] View-Invariant Full-Body Gesture Recognition via Multi linear Analysis of Voxel Data
    Peng, Bo
    Qian, Gang
    Rajko, Stjepan
    2009 THIRD ACM/IEEE INTERNATIONAL CONFERENCE ON DISTRIBUTED SMART CAMERAS, 2009, : 44 - 51
  • [14] Inverse kinematics for full-body self representation in VR-based cognitive rehabilitation
    Wagnerberger, Larissa
    Runde, Detlef
    Lafci, Mustafa Tevfik
    Przewozny, David
    Bosse, Sebastian
    Chojecki, Paul
    23RD IEEE INTERNATIONAL SYMPOSIUM ON MULTIMEDIA (ISM 2021), 2021, : 123 - 129
  • [15] Real-time Full-body Motion Reconstruction and Recognition for Off-the-Shelf VR Devices
    Jiang, Fan
    Yang, Xubo
    Feng, Lele
    PROCEEDINGS VRCAI 2016: 15TH ACM SIGGRAPH CONFERENCE ON VIRTUAL-REALITY CONTINUUM AND ITS APPLICATIONS IN INDUSTRY, 2016, : 309 - 318
  • [16] Systematic Review of Design Guidelines for Full-Body Interactive Games
    Subramanian, Sruti
    Skjaeret-Maroni, Nina
    Dahl, Yngve
    INTERACTING WITH COMPUTERS, 2020, 32 (04) : 367 - 406
  • [17] Hierarchical method for interactive gesture modeling and recognition towards VR application
    Wang, Xiying
    Dai, Guozhong
    Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics, 2007, 19 (10): : 1334 - 1341
  • [18] HumanoidBot: Full-Body Humanoid Chitchat System
    Seppelfelt, Gabriel D. C.
    Asaka, Tomoki
    Nagai, Takayuki
    Yukizaki, Soh
    2022 IEEE-RAS 21ST INTERNATIONAL CONFERENCE ON HUMANOID ROBOTS (HUMANOIDS), 2022, : 231 - 237
  • [19] Augmenting Gesture Animation with Motion Capture Data to Provide Full-Body Engagement
    Luo, Pengcheng
    Kipp, Michael
    Neff, Michael
    INTELLIGENT VIRTUAL AGENTS, PROCEEDINGS, 2009, 5773 : 405 - +
  • [20] Human Body Full-body Motion Gesture Image Feature Capture in Mobile Sensor Networks
    Yang, Zhaolin
    Ambati, Loknath Sai
    MOBILE NETWORKS & APPLICATIONS, 2024,