MacBook

A student made a touch screen for a MacBook for $ 1. How to make the same

A student made a touch screen for a MacBook for $ 1. How to make the same
After a little refinement of Kwok’s technology, the guys created Project Sistine.

What it is and how it works

This is a special system that helps the MacBook screen to understand exactly where the user is touching.

The idea is to place a small mirror in front of the built-in macbook camera so that it looks at the computer screen at an acute angle.

This way the camera can see the user’s fingers. And with the help of computer vision, transform the video stream into commands for touch control.

A student made a touch screen for a MacBook for $ 1. How to make the same
The resulting device for reading MacBook screen touches

As a result, to implement the plan it took:

• hot glue
• miniature mirror
• hard paper plate (this is not a joke)
• door hinges

With their help, the mirror is mounted above the MacBook on a makeshift mount. So it was going:

A student made a touch screen for a MacBook for $ 1. How to make the same
Then the students set about creating software. It had to determine the color of the skin, the size of the finger along the upper (reflection on the screen) and lower (real finger shot by the camera) contour.

Next, the algorithm estimates the middle line between them and takes it for the touch point to the laptop screen .

A student made a touch screen for a MacBook for $ 1. How to make the same
So the camera reads the touch

A student made a touch screen for a MacBook for $ 1. How to make the same
After the initial calibration of the system, the camera and software will learn to adequately estimate the distance from the finger to the screen and recognize the coordinates of the touch point using the RANSAC method.

RANSAC – a method for estimating model parameters based on random samples

Total

im g In the final prototype, the developers converted touch and finger movements into mouse commands. When creating the model, a camera with a resolution of 480p was used. And the greater the resolution of the camera, the more accurately the movements will be read.

The creators published the source code for the computer vision system on GitHub. There are also detailed installation instructions. [AnishaTalye]

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