Low-Cost Wireless Intelligent Two Hand Gesture Recognition System

被引:0
作者
Natesha, Aswin [1 ]
Rajan, Gandhi [1 ]
Thiagarajan, Balasubramanian [3 ]
Vijayaraghavan, Vineeth [2 ]
机构
[1] Solarill Fdn, Madras, Tamil Nadu, India
[2] Solarill Fdn, Res & Outreach, Madras, Tamil Nadu, India
[3] Sri Venkateswara Coll Engn, Madras, Tamil Nadu, India
来源
2017 11TH ANNUAL IEEE INTERNATIONAL SYSTEMS CONFERENCE (SYSCON) | 2017年
关键词
Bluetooth Low Energy (BLE); calibration; gesture recognition; microcontrollers; open source hardware; sensors; sign language recognition;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper elucidates the design and implementation of a low-cost wireless intelligent two hand gesture recognition system. The proposed system consists of a primary and secondary sub-system which work in tandem to recognize static gestures signed by the user. Each of the sub-systems consists of a sensory glove, embedded with custom made, low-cost flex and contact sensors interfaced with a ATMega328 microcontroller. The two sub-systems are wirelessly inter-connected through a pair of TI's CC2541 Bluetooth Low Energy (BLE) modules. The system recognizes gestures with the help of a Dual-mode Intelligent Agent (DIA) which operates in Identification Mode (IM) and intelligently switches to Enhanced Identification Mode (EIM) when the gesture fails to get recognized in IM. The EIM incorporates a Bit Stream Error Elimination (BSEE) algorithm which enhances the gesture recognition accuracy without the addition of any external hardware. The performance of the system was evaluated using a data set comprising of 196 static gestures from eight globally used sign languages. The system efficiency was found to be 80.06% in IM and was enhanced to 93.16% in EIM. The cost of the proposed system in prototype stage is USD 22, which the authors believe could be realized at under USD 10 on commercialization.
引用
收藏
页码:300 / 305
页数:6
相关论文
共 12 条
[1]  
[Anonymous], SIGN LANGUAGE
[2]   Recognizing postures in Vietnamese sign language with MEMS accelerometers [J].
Bui, The Duy ;
Nguyen, Long Thang .
IEEE SENSORS JOURNAL, 2007, 7 (5-6) :707-712
[3]  
Chouhan Tushar, 2014, 2014 IEEE Global Humanitarian Technology Conference - South Asia Satellite (GHTC-SAS), P105, DOI 10.1109/GHTC-SAS.2014.6967567
[4]   A real-time continuous gesture recognition system for sign language [J].
Liang, RH ;
Ouhyoung, M .
AUTOMATIC FACE AND GESTURE RECOGNITION - THIRD IEEE INTERNATIONAL CONFERENCE PROCEEDINGS, 1998, :558-567
[5]  
Mehdi SA, 2002, ICONIP'02: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING, P2204
[6]  
Phi LT, 2015, INT C CONTR AUTOMAT, P1555, DOI 10.1109/ICCAS.2015.7364604
[7]   Hand Talk-Implementation of a Gesture Recognizing Glove [J].
Preetham, Celestine ;
Ramakrishnan, Girish ;
Kumar, Sujan ;
Tamse, Anish ;
Krishnapura, Nagendra .
2013 TEXAS INSTRUMENTS INDIA EDUCATORS' CONFERENCE (TIIEC 2013), 2013, :328-331
[8]  
Rishikanth C, 2014, IEEE GLOB HUMANIT C, P628, DOI 10.1109/GHTC.2014.6970349
[9]  
Sekar H., 2016, 10 ANN INT SYST C SY, DOI [10.1109/SYSCON.2016.7490642, DOI 10.1109/SYSCON.2016.7490642]
[10]   A SURVEY OF GLOVE-BASED INPUT [J].
STURMAN, DJ ;
ZELTZER, D .
IEEE COMPUTER GRAPHICS AND APPLICATIONS, 1994, 14 (01) :30-39