Hand and Face Gesture Controlled Video Player
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BrewV is a computer vision based video player which uses face and hand gestures to control the functionality of a videoplayer like forward seeking , volume control etc. The PyQt5 library is used for the design the Gui and libvlc python bindings is used for implementing video player functionalities. ...learn more
Project status: Published/In Market
Overview / Usage
The project tracks hand and face gestures made by the users using Haar cascade and based on that the video player is given signal either to seek forward/backward , volume control etc. The usage details are mentioned in the github repository.
The project has been tested on MacOs and linux and the installation steps are given in the github repository.
In the version 2 of the player I would use deep learning techniques like RCNN to track the gestures.
Methodology / Approach
The methodology used to solve the problem is to extract the gestures from each frame using Haar cascade and run a thread parallel to it to intimate the player whenever gestures are detected.
Technologies Used
The video player uses lib vlc python bindings and PyQt5 for GUI. The AI part of this is written in C++ which uses OpenCV library.