During the COVID-19 pandemic, unemployment in the US surged, highlighting the need for accessible and affordable professional training. Traditional training programs for jobs like industrial labor and auto mechanics can be prohibitively expensive, ranging from $1,000 to $20,000. Existing solutions, such as online courses, lack interactivity, while current virtual and augmented reality options require specific hardware and still depend on physical equipment.
This project addresses these challenges by developing a Unity-based mobile app that uses realistic and interactive augmented reality to enhance educational engagement and provide accessible training. It uses NatML to track hand landmarks before being interpreted by a custom algorithm to identify hand pose.
GitHub Repo: https://github.com/jzfcoder/HandTracking