Getting to know the hands’ gestures

How to get the gestures needed?
Generally, in order to detect hand and extract gestures from dymanic background environments, some algrithms such as color segment and some kinds of ‘mean’ algrithms are neccessary, indeed. And, as far as i have learned until now, i found 2 methods to effectively extract target gestures from background images. Those methods are color segment, motion detection and more advanced sensing like infrared detecting integrating with motion or color. This step is quit easy to archive because of the limited algrithms and hand characters which include color, motion and what? Nothing! Probably temperature, but that is not so universal.

What chatacters could be used for recognizing gestures?
  So, if the gestures are extracted from the complicated background images, the next step would be recognize them. Recognition is not as simple as detection which you just do some filter work. It needs several unique characters from the detected images. Most of the time, these characters probably contain: 1) angle – detecting the rotation   2) size – detecting the area   3)  peak and valley which is specific for the open hand  4) moving speed and direction. 

Author: Andol Li

A HCI researcher, a digital media lecturer, an information product designer, and a python/php/java coder.

3 Comments On “ Getting to know the hands’ gestures”

  1. hello sir,
    here the drawn contour is not exact , it is distorted in most of the hand positions.
    It might be due to using CV_MEDIAN smoothing effect,can we use any other smoothing feature like GAUSSIAN etc… how can it be modified to get exact outline of hand gesture?

  2. hello sir,
    I am trying to make a program for fingertip detection in opencv… but i don’t know where to start from ??
    can u please give the required steps needed to start the project ??

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