Gesture-Based Multi-Parameter Controller for Mac using Machine Learning and Computer Vision
Author(s):
Vrushabh Sachin Shah
Keywords:
Machine Learning, Computer Vision, Mac, Media Pipe, Gesture Detection, AppleScript
Abstract
The proposed system uses a lightweight framework called Media pipe which not only allows for detection of hands but can classify whether it is the left or right hand and represents this data as 21 data points representing the various parts of the hand. With these uniquely identified 21 data points for each hand, we can identify different gestures and assign some functionality for them. The system checks the position of fingers, which of them are raised, and which are not to uniquely identify the hand gestures. It is capable of controlling multiple basic functionalities like increasing or decreasing the volume level, controlling the brightness intensity, a virtual mouse, zooming in and out, and scrolling in all four directions. These functionalities are divided between the gestures created by the left and right hand. This particularly comes in handy when watching a movie or video where the laptop is kept at a distance or connected to a TV and reaching the keyboard to control all these functionalities continuously becomes an irritating task.
Article Details
Unique Paper ID: 153505

Publication Volume & Issue: Volume 8, Issue 7

Page(s): 326 - 329
Article Preview & Download


Share This Article

Join our RMS

Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Call For Paper

Volume 10 Issue 10

Last Date for paper submitting for March Issue is 25 June 2024

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews