Gloved and Free Hand Tracking based Hand Gesture Recognition

被引:0
|
作者
Mazumdar, Dharani [1 ]
Talukdar, Anjan Kumar [1 ]
Sarma, Kandarpa Kumar [2 ]
机构
[1] Gauhati Univ, Dept Elect & Commun Engn, Gauhati 14, Assam, India
[2] Gauhati Univ, Dept Elect & Commun Technol, Gauhati 14, Assam, India
来源
2013 1ST INTERNATIONAL CONFERENCE ON EMERGING TRENDS AND APPLICATIONS IN COMPUTER SCIENCE (ICETACS) | 2013年
关键词
Hand gesture recognition; Segmentation; Tracking; Complex background; SEGMENTATION;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Hand gesture recognition system can be used for human-computer interaction (HCI). The use of hand gestures provides an attractive alternative to cumbersome interface devices for HCI. Proper hand segmentation from the background and other body parts of the video is the primary requirement for the design of a hand-gesture based application. These video frames can be captured from a low cost webcam (camera) for use in a vision based gesture recognition technique. This paper discusses about continuous hand gesture recognition. It reports a robust and efficient hand tracking as well as segmentation algorithm where a new method, based on wearing glove on hand is utilized. We have also focused on another tracking algorithm, which is based on skin colour of the palm part of the hand i.e. free hand tracking. A comparative study between two tracking methods is presented in this paper. A finger tip can be segmented for proper tracking in spite of the full hand part. Hence, this technique allows the hand (excepting the segmented finger) to move freely during the tracking time also. Problems such as skin colour detection, complexity from large numbers of people in front of the camera, complex background removal and variable lighting condition are found to be efficiently handled by the system. Noise present in the segmented image due to dynamic background can be removed with the help of this adaptive technique which is found to be effective for the application conceived.
引用
收藏
页码:197 / 202
页数:6
相关论文
共 50 条
  • [21] Indonesian Sign Language Recognition Based on Shape of Hand Gesture
    Indra, Dolly
    Purnawansyah
    Madenda, Sarifuddin
    Wibowo, Eri Prasetyo
    FIFTH INFORMATION SYSTEMS INTERNATIONAL CONFERENCE, 2019, 161 : 74 - 81
  • [22] Hand Gesture Recognition Based on Computer Vision: A Review of Techniques
    Oudah, Munir
    Al-Naji, Ali
    Chahl, Javaan
    JOURNAL OF IMAGING, 2020, 6 (08)
  • [23] Recent methods and databases in vision-based hand gesture recognition: A review
    Pisharady, Pramod Kumar
    Saerbeck, Martin
    COMPUTER VISION AND IMAGE UNDERSTANDING, 2015, 141 : 152 - 165
  • [24] Recognition of Static Hand Gesture
    Sadeddine, Khadidja
    Djeradi, Rachida
    Chelali, Fatma Zohra
    Djeradi, Amar
    PROCEEDINGS OF 2018 6TH INTERNATIONAL CONFERENCE ON MULTIMEDIA COMPUTING AND SYSTEMS (ICMCS), 2018, : 368 - 373
  • [25] A Method for Hand Gesture Recognition
    Shukla, Jaya
    Dwivedi, Ashutosh
    2014 FOURTH INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS AND NETWORK TECHNOLOGIES (CSNT), 2014, : 919 - 923
  • [26] A Survey on Hand Gesture Recognition
    Chen, Lingchen
    Wang, Feng
    Deng, Hui
    Ji, Kaifan
    2013 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCES AND APPLICATIONS (CSA), 2013, : 313 - 316
  • [27] Dynamic Hand Gesture Recognition Using the Skeleton of the Hand
    Bogdan Ionescu
    Didier Coquin
    Patrick Lambert
    Vasile Buzuloiu
    EURASIP Journal on Advances in Signal Processing, 2005
  • [28] Dynamic hand gesture recognition using the skeleton of the hand
    Ionescu, B
    Coquin, D
    Lambert, P
    Buzuloiu, V
    EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING, 2005, 2005 (13) : 2101 - 2109
  • [29] Hand Gesture Recognition in Complex Background Based on Convolutional Pose Machine and Fuzzy Gaussian Mixture Models
    Zhang, Tong
    Lin, Huifeng
    Ju, Zhaojie
    Yang, Chenguang
    INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2020, 22 (04) : 1330 - 1341
  • [30] A comparative study of advanced technologies and methods in hand gesture analysis and recognition systems
    Rahman, Md Mijanur
    Uzzaman, Ashik
    Khatun, Fatema
    Aktaruzzaman, Md
    Siddique, Nazmul
    EXPERT SYSTEMS WITH APPLICATIONS, 2025, 266