Hand part labeling and gesture recognition from RGB-D data

被引：0
|
作者：
Yao, Yuan [1 ,2 ]
Zhang, Linjian [1 ]
Qiao, Wenbao [1 ]
机构：
[1] Rapid Manufacture Engineering Center, Shanghai University, Shanghai 200444, China
[2] Shanghai Key Laboratory of Manufacturing Automation and Robotics, Shanghai 200072, China
来源：
Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics | 2013年 / 25卷 / 12期
关键词：
Palmprint recognition;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
For depth sensor based hand gesture recognition, how to collect training data and built a gesture database with suitable size are challenging tasks. In this paper, we present a semi-automatic labeling scheme for establishing the real hand gesture dataset. A framework for developing hand gesture driven desktop applications is designed based on this scheme, which use RGB-D sensor as input. Moreover, a hand contour model is proposed to simplify the gesture matching process and reduce the computational complexity. The experimental evaluations and a demo application demonstrate the effectiveness of this framework.
引用
收藏
页码：1810 / 1817
相关论文
共 50 条
  • [31] Contextual object category recognition for RGB-D scene labeling
    Ali, Haider
    Shafait, Faisal
    Giannakidou, Eirini
    Vakali, Athena
    Figueroa, Nadia
    Varvadoukas, Theodoros
    Mavridis, Nikolaos
    ROBOTICS AND AUTONOMOUS SYSTEMS, 2014, 62 (02) : 241 - 256
  • [32] Object Recognition in Noisy RGB-D Data
    Carlos Rangel, Jose
    Morell, Vicente
    Cazorla, Miguel
    Orts-Escolano, Sergio
    Garcia Rodriguez, Jose
    BIOINSPIRED COMPUTATION IN ARTIFICIAL SYSTEMS, PT II, 2015, 9108 : 261 - 270
  • [33] Explore Efficient Local Features from RGB-D Data for One-Shot Learning Gesture Recognition
    Wan, Jun
    Guo, Guodong
    Li, Stan Z.
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2016, 38 (08) : 1626 - 1639
  • [34] A Dynamic Gesture Recognition Algorithm based on Feature Fusion from RGB-D Sensor
    Wang, Xia
    Chen, Peng
    Wu, Man
    Niu, Yong
    PROCEEDINGS OF 2022 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (IEEE ICMA 2022), 2022, : 1040 - 1045
  • [35] RGB-D static gesture recognition based on convolutional neural network
    Xie, Bin
    He, Xiaoyu
    Li, Yi
    JOURNAL OF ENGINEERING-JOE, 2018, (16): : 1515 - 1520
  • [36] RGB-D Object Recognition from Hand-Held Object Teaching
    Qiao, Leixian
    Li, Xue
    Jiang, Shuqiang
    8TH INTERNATIONAL CONFERENCE ON INTERNET MULTIMEDIA COMPUTING AND SERVICE (ICIMCS2016), 2016, : 31 - 34
  • [37] Real-time hand status recognition from RGB-D imagery
    Bagdanov, Andrew D.
    Del Bimbo, Alberto
    Seidenari, Lorenzo
    Usai, Lorenzo
    2012 21ST INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR 2012), 2012, : 2456 - 2459
  • [38] ZS-GR: zero-shot gesture recognition from RGB-D videos
    Rastgoo, Razieh
    Kiani, Kourosh
    Escalera, Sergio
    MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (28) : 43781 - 43796
  • [39] ZS-GR: zero-shot gesture recognition from RGB-D videos
    Razieh Rastgoo
    Kourosh Kiani
    Sergio Escalera
    Multimedia Tools and Applications, 2023, 82 : 43781 - 43796
  • [40] Object Class and Instance Recognition on RGB-D Data
    Seib, Viktor
    Christ-Friedmann, Susanne
    Thierfelder, Susanne
    Paulus, Dietrich
    SIXTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2013), 2013, 9067
12345