The app uses the smartphone's built-in camera to register its environment.
By mimicking the firing of a pistol, for example, a user can switch to another browser tab, change the map's view from satellite to standard, or shoot down enemy planes in a game.
Spreading out fingers magnifies a section of a map or scrolls the page of a book forward.
The information that the app registers - the shape of the gesture, the parts of the hand - is reduced to a simple outline that is classified according to stored gestures.
The app, developed by Jie Song, a master's student in the working group headed by by Otmar Hilliges, Professor of Computer Science at ETH Zurich, then executes the command associated with the gesture it observes.
It also recognises the hand's distance from the camera and warns the user when the hand is either too close or too far away.
"Many movement-recognition programmes need plenty of processor and memory power," said Hilliges, adding that their new algorithm uses a far smaller portion of computer memory and is thus ideal for smartphones.
The app's minimal processing footprint means it could also run on smart watches or in augmented-reality glasses.
The app currently recognises six different gestures and executes their corresponding commands.