Vision-based real-time game interface

In this paper, we will introduce a fast and robust method of constituting a probability map by extracting foreground object from background image which is basic technology to be applied to vision-based real-time game interaction. We implement a neural network with one hidden layer to recognize a motion of the probability map. In this process, we extract the foreground probability map which is robust against change of illumination using local binary pattern and improve the speed using integral histogram. Also, we use a novel Gaussian window frame mask which can be applied fast in the integral histogram process and reduce noise by adaptive Gaussian sigma value depending on the strength of edge. In the following, experiments are carried out and satisfactory results are obtained which indicate the fast and robust conditions.