Project info
- Developer Steven Anderson
- Showcase year 2021
- Programme Computer Game Applications Development
Synopsis
Evaluating how effective machine learning can be at aiding video game accessibility by using gesture recognition as the input method to control a game application. Using Tensorflow, I created a classification algorithm capable of classifying multiple hand gestures (E.g., open palm, fist, or thumbs up). I made a game to test the algorithm, where the gestures are used for input. The user must copy the gesture shown above an enemy's head and press the action button to defeat them, allowing progression through the game. Classic arcade shooter games inspired the game application; this allowed for a game that was not too fast-paced for gesture recognition to be counterproductive.
Improving Video Game Accessibility Through Gesture Recognition
This project aims to evaluate if machine learning is an effective tool at aiding accessibility to video games through gesture recognition.
Motivation
Older family members used to love playing video games but, as they got older, they found it harder to play the games they enjoyed due to finger mobility issues with the standard input devices that most platforms use.
Credits
鈥淚mproving Video Game Accessibility Through Gesture Recognition鈥� is a 2021 Digital Graduate Show project by聽Steven Anderson, a Computer Game Applications Development student at 尤物视频.聽聽聽聽聽聽
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