Abstract: Development of autonomic chess-playing robots creates
several interesting computer vision problems, including plane
calibration and object recognition. Various solutions have been
attempted, but most either require a modified chess set or place
unreasonable constraints on board conditions and camera angles.
A more general solution uses computer vision to automatically
determine arbitrary chessboard location and identify chessmen
on a standard, unmodified chess set. Although much work has
been devoted to probabilistic image recognition in general, this
paper presents a novel solution to the specific chessboard location
problem that is accurate, less restrictive, and relatively time
efficient.
Abstract: Multiplayer games require a networking connection that
delivers results in near real-time, as well as enough reliability
to ensure a playable experience for the user. This project
explores some of those issues by implementing a simple
capture-the-flag style 3D game, entitled Kittenstrophic, over a
UDP protocol, using a classic client-server model to produce
a game experience with low overhead and quick response.
Abstract: Human-interface devices have begun a trend towards abstracting the user interface into more natural physical actions. Sonar sensors detect the approximate distance of an object from the sensor. By interpolating the signal between two sensors, the user can control a one-dimensional axis. Using the classic video game of pong as an example, this project demonstrates the viability of these sensors, and also examines future uses of similar devices.
