Intelligent Connected Platform

Gesture Recognition for Media Controls


Gesture is one of the most vivid and dramatic way of communications between human and computer/edge device. Hence, there has been a growing interest to create easy-to-use interfaces by directly utilizing the natural communication and management skills of humans. Adopting hand gesture as an interface in HCI will allow the deployment of a wide range of applications without any physical contact with the computing environments. The main purpose of gesture recognition is to identify a particular human gesture and convey information to the computer/edge device. Overall aim is to make the computer understand human gestures, to control remotely through hand postures a wide variety of devices.

  • This Application presents a hand gesture interface for controlling media player using QueSSence.
  • QueSSence recognizes a set of four specific hand gestures, namely: Play, Stop, Volume Increase, and Volume Decrease by using K-Nearest Neighbor algorithm.
  • Developed algorithm is based on four phases, Data acquisition, Data segmentation, Features extraction, and Classification.
  • We design an affective technique for hand gesture recognition to control media player using the properties of accelerometer signals generated by human hand movements.
  • We tested and evaluate the effectiveness of algorithm in real time to four specific hand gestures, namely: Play, Stop, Volume Increasing, and Volume Decreasing.