Sight beyond sight in AR based on non-visible signals
Bachelor Thesis, Master Thesis
Non-visible signals (such as sound) have been used in the past to recognize people, and people's activities. In many cases these signals are distinguishable and useful for recognition tasks even when objects obstruct the user's direct view. With such approaches as basis, it is possible to envision cases in which what is being occluded can be rendered into the user's visual field through augmented reality (AR).
Goal
Devise and implement an approach that allows to depict in AR dynamic live entities behind visual obstacles (such as a wall) based on non-visible signals (e.g., sound).
Requirements
- Programming experience required, particularly with Xcode for iOS preferred.
- Experience with Apple's ARKit can be helpful
- Some hands-on experience in machine learning can be helpful
- Eagerness to learn and work hard
