Gaming Video Quality

Assessing video quality in gaming, particularly from user-generated content and cloud gaming streams, is a growing research area aiming to develop accurate, no-reference quality metrics. Current efforts focus on creating models that leverage both traditional image statistics and deep learning techniques (like convolutional neural networks) to predict perceived quality, often using support vector regression for final quality scores. These advancements are crucial for optimizing video compression, streaming delivery, and enhancing the overall user experience in the rapidly expanding gaming video market.