Total views : 201
Transmission and Detection of Electromagnetic Waves for Gesture Recognition
Hand gesture technology makes users’ lives simpler, achieving “hands free” interaction through eliminating the need to hold or press the device. Since the need of human computer interaction has increased to a great-extent, such a technique needs to be devised that do not depend on Vision or Wearable sensors approach. This paper is a sincere attempt to recognize gestures using EM field detection approach. This requires only an EM field transmitter and a detector (receiver). The novelty of this approach is, it not only reduces extra cost for wearable or vision based sensors but would also account for a wide range of coverage area. In addition to this, method to recognize gestures through EM Waves with the help of a laser light is also practically implemented. The demonstration of this method is illustrated with the help of Macromedia Flash Player. This theory will certainly reduce the cost factor and add to the simplicity of the current human computer interactions.
Detector, Doppler Shift, Electromagnetic, Flux Points, Gesture Recognition, Light Sensor.
- Holzrichter JF, Ng LC and Livermore L. Speech Articulator and User Gesture Measurements Using Micropower, Interferometric EM-Sensors. Institute of Electrical and Electronics Engineers. 2001 May; p. 21-3.
- Pu Q, Gupta S, Gollakota S and Patel S. Whole-home gesture recognition using wireless signals. 2013 July; p. 485-86.
- Xu R, Zhou S and Li W. MEMS Accelerometer Based Non-Specific-User Hand Gesture Recognition. Institute of Electrical and Electronics Engineers Sensors Journal. 2012 May; 12(5):1166-73.
- Nachamai M. Alphabet Recognition of American sign language: A hand gesture recognition approach using SIFT algorithm. International Journal of Artificial Intelligence & Applications. 2013 January; 4(1):105-15.
- Avraam M. Static Gesture Recognition Combining Graph and Appearance Features. International Journal of Advanced Research in Artificial Intelligence. 2014 May; 3(2):1-4.
- Mane SM, Kambli RA, Kazi FS, Singh NM. Hand Motion Recognition From Single Channel Surface EMG Using Wavelet & Artificial Neural Network. Procedia Computer Science. 2015 April; 49(2015):58-65.
- Sharma RP and Verma GK. Human Computer Interaction using Hand Gesture. Procedia Computer Science. 2015 June; 54(2015):721-27.
- Chakravarthi MK, Tiwari RK and Handa S. Accelerometer Based Static Gesture Recognition and Mobile Monitoring System Using Neural Networks. Procedia Computer Science. 2015 October; 70(2015):683-87.
- Lalithamani N. Gesture Control Using Single Camera for PC. Procedia Computer Science. 2016 Feburary; 78(2016):146-52.
- Kanchana Devi P, Raji A and Srinivasan G. Gesture Recognition for Physically Challenged. Indian Journal of Science and Technology. 2016 April; 9(16):1-5.
- Deepa A, Sasipraba T. Challenging Aspects for Facial Feature Extraction and Age Estimation. Indian Journal of Science and Technology. 2016 January; 9(4):1-6
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.