hand-gesture-recognition's Introduction

Hand Gesture Recognition

• Extract and segment hand region from the video sequence.

• Recognize the number of fingers from the segmented hand region by using Convex Hull.

Getting Started

How to use

git clone https://github.com/aakashjhawar/Hand-Gesture-Recognition.git
cd Hand-Gesture-Recognition

Run the Finger_count.ipynb Jupyter Notebook

sudo apt-get install python-opencv

Strategy for counting fingers
- Garb an ROI (Region of interest)
  - Calculate a running average background value for 60 frames of video
  - Once average value is found, then the hand can enter the ROI
Set a ROI and calculate the average running value for some amount of frames
Then once a hand enters, we can detect change and apply thresholding
Strategy for counting fingers * Once the hand enters the ROI, we will use a Convel Hull to draw a polygon around the hand * Using some maths, we'll calculate the center of the hand against the angle of outer points to infer finger count
The next step is to use thresholding to grab the hand segment from the ROI
Now that we have the hand segment, the next step is to actually count the fingers behind held up
We can do this by utilizing a Convex Hull
A convex hull draws a polygon by connecting points around the most external points in a frame
In our case, this set of points is actually just our threshold image of a hand.
We can expect a general shape of our polygon to be something like
Then using a ratio of that distance we create a circle
Any points outside of this circle far away enough from the bottom, should be extended fingers