CONTENT-ADAPTIVE SIGNAL-TO NOISE-RATIO-GUIDED TWO-PASS VIDEO ENCODING FOR CLOUD GAMING
Techniques for encoding game content for real-time cloud-gaming, and more specifically to using an adaptive statistical model in a moving window of previous frames up to a current frame to adaptively compute a lower-bound of a quantization parameter (QP) that corresponds to a chosen peak signal to n...
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creator | ERKIN, Beril HONG, Danny XIE, Richard TAHASILDAR, Ramachandra SUKHANOV, Alex |
description | Techniques for encoding game content for real-time cloud-gaming, and more specifically to using an adaptive statistical model in a moving window of previous frames up to a current frame to adaptively compute a lower-bound of a quantization parameter (QP) that corresponds to a chosen peak signal to noise ratio (PSNR) target. The result of this PSNR-guided encoding is significantly reducing the size of encoded frames (i.e., undershooting a target bit rate when there are no subjective quality losses on those frames using their PSNR as the guidance). These reductions mitigate bandwidth issues and improve the overall user experience because less bits transferred results in faster network transmission and decoding, as well as less platform overhead. |
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subjects | ELECTRIC COMMUNICATION TECHNIQUE ELECTRICITY PICTORIAL COMMUNICATION, e.g. TELEVISION |
title | CONTENT-ADAPTIVE SIGNAL-TO NOISE-RATIO-GUIDED TWO-PASS VIDEO ENCODING FOR CLOUD GAMING |
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