Markerless Vision-Based Tracking for Interactive Augmented Reality Game
Chutisant Kerdvibulvech
Volume 2010 (2010), Article ID 751615, International Journal of Interactive Worlds, 14 pages
In
this paper, we present an interactive augmented reality (AR) game for
tracking a remote-controlled car controlled by players. We propose it
as a new markerless framework for tracking a colored remote-controlled
car by integrating a Bayesian classifier into particle filters. This
adds the useful abilities of automatic track initiation and recovery
from tracking failures in a cluttered background. A Bayesian classifier
is utilized to determine the car‘s color probability before tracking.
In addition, by using the online adaptation of color probabilities,
this method is able to cope well with luminance changes. We calculate
the projection matrix as an online process. The method presented can be
used to develop the real-time game of AR to remote-controlled car
playing. The application can entertain players interactively by
controlling the car to the augmented items. A user study is conducted
to evaluate the effectiveness of the aforementioned application.
Keywords: Augmented Reality, Bayesian Classifier, Interactive Game, Particle Filter
