A Hybrid Machine Learning Approach for Efficient Deployment of Virtual Screens based on Unity

  • M.Vijayasanthi et al.


In the current generation computing technology, the virtual screens of the unity are generated in a
manual process. With the advent of machine learning the automation of computing paradigms are
leveraged through the enforcement of deploying efficient machine learning algorithms. The main
objective of this article is to properly engaging efficient machine learning algorithm for rapid
deployment of unity virtual screens. Original k-means clustering algorithm chooses initial clustering
centroids randomly, and it may lead the converge of clustering results to local optimal solution.
According to the Unity terrain data distribution, the scope of the initial clustering centroids can be
determined, so we choose k most remote data point as the initial clustering centroids. The
experimental results show that the algorithm can guarantee the clustering quality and reduce the
number of iterations effectively, and it can be used to generate Unity virtual scenesautomatically