PROJECT TITLE :
Audio–Visual Emotion-Aware Cloud Gaming Framework
ABSTRACT:
The promising potential and rising applications of cloud gaming have drawn increasing interest from academia, industry, and the overall public. However, providing a high-quality gaming expertise within the cloud gaming framework is a challenging task because of the tradeoff between resource consumption and player emotion, which is laid low with the sport screen. We tend to tackle this drawback by leveraging emotion-aware screen effects in the cloud gaming framework and combining them with remote show technology. The primary stage in the framework is the educational or training stage, that establishes a relationship between screen features and emotions using Gaussian mixture model-based mostly classifiers. Within the operating stage, a linear programming model provides applicable screen changes primarily based on the $64000-time user emotion obtained in the primary stage. Our experiments demonstrate the effectiveness of the proposed framework. The results show that our proposed framework will give a high quality gaming expertise whereas generating a suitable quantity of workload for the cloud server in terms of resource consumption.
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