tuipong - a tangible and multitouch pong game

 

the game

tuipong is a tabletop pong game that uses both tangible user interfaces (TUI) and multitouch as input. the pong game is augmented with a new physics engine based on the fisica library for processing designed by ricard marxer.

the physics engine allows players to rotate the paddle at 360 degrees, and use the angular velocity of the paddle to deflect the ball at different directions and speeds. i developed this interactive tabletop game as part of my master thesis in 2011.

 

A picture of the TUIPONG game: (left) a single-player pong game where the scope is to absorb the balls that come at different speeds to test one's reflexes ; (right) the augmented pong with the possibility to deflect the ball at 360 degrees.

 

the game mechanics

in tuipong there are two game modalities: (1) a “classical” pong augmented with rotation motions and (2) a quickness game to test reflexes and reaction times.

In the quickness game, the player can test their reflexes and improve their reaction time skills as they are challenged with increasing speeds and difficult levels.

In the classical/augmented pong game, the player can test their gaming skills in a game of pong, but with the possibility to move the paddle in any direction as well as rotate it to deflect the ball at different angles.

 
 

The system architecture

The hardware setup used in tuipong is the same as the ReacTable. This hardware consists of: (1) a round table with a luminous acrylic transparent surface, (2) two arrays of Infra-Red lights, (3) a BenQ MX710 projector using DLP technology, with a native resolution XGA of 1024 x 768 and a noise level of ≈30.0 db, (4) a mirror positioned in front of the projector, and (5) an Allied Guppy38 F-033B/C camera, with a Sony ICX424 CCD sensor and a resolution of 60 fps.

To provide sound feedback, the tabletop structure was embedded with pair of regular studio speakers. The fingers and object tracking software, as well as the two applications programmed in Processing, run on a mac computer with MacOSX Leopard. Finger and fiducial marker detection were achieved using the reacTIVision tracking library. to extract Information about position, angle, speed, and acceleration were extracted using the TUIO library.