• DocumentCode
    1789115
  • Title

    S control: Accelerometer-based gesture recognition for media control

  • Author

    Chudgar, Haresh S. ; Mukherjee, Sayan ; Sharma, Kamna

  • Author_Institution
    DMC R&D Center, Samsung R&D Inst., Bangalore, India
  • fYear
    2014
  • fDate
    10-11 Oct. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Wearable devices such as Samsung Galaxy Gear enable intuitive interaction with media devices via hand gestures. The hand gestures are detected using the inertial sensors present in wearable devices. Existing sensor based gesture detection algorithms have limitations which prevent its use in smart wearable devices and smart phones. There are two major limitations, one is gesture spotting in a stream of continuous sensor data and another is the amount of training required to arrive at acceptable gesture detection accuracy. We discuss these and other limitations in detail and propose an algorithm to overcome them. Further the paper discusses a method of finding the intensity of the performed gesture which can be used to improve the user experience.
  • Keywords
    accelerometers; gesture recognition; human computer interaction; mobile computing; wearable computers; S control; Samsung Galaxy Gear; accelerometer-based gesture recognition; gesture spotting; inertial sensors; media control; media devices; sensor based gesture detection algorithms; smart phones; smart wearable devices; Accelerometers; Accuracy; Arrays; Gesture recognition; Intelligent sensors; Training; Accelerometer; Dynamic Time Warping; Gestures; Human Machine Interaction; Inertial Sensors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Electronics, Computers and Communications (ICAECC), 2014 International Conference on
  • Conference_Location
    Bangalore
  • Type

    conf

  • DOI
    10.1109/ICAECC.2014.7002459
  • Filename
    7002459