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On Combining Temporal Scaling and Quality Scaling for Streaming MPEG. Huahui Wu , Mark Claypool, Robert Kinicki Computer Science, Worcester Polytechnic Institute. Introduction. Streaming video Bitrate > Network capacity Media Scaling Temporal Scaling (TS) or Quality Scaling (QS)
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On Combining Temporal Scaling and Quality Scaling for Streaming MPEG Huahui Wu, Mark Claypool, Robert Kinicki Computer Science, Worcester Polytechnic Institute
Introduction • Streaming video • Bitrate > Network capacity • Media Scaling • Temporal Scaling (TS) or Quality Scaling (QS) • Packet loss • Forward Error Correction (FEC) • Operations Research algorithm • To satisfy capacity constraint • To maximize perceived quality • Previous research • Temporal Scaling [TOMCCAP 05] • Quality Scaling [NOSSDAV 05] • This work • Combines Temporal Scaling and Quality Scaling NOSSDAV06
Outline • Introduction • Model • Streaming Bitrate (cost) • Video Quality (benefit) • Algorithm • Experiments • Conclusions NOSSDAV06
System Layers and Parameters NOSSDAV06
Streaming Bitrate • Total streaming bitrate, including video packets and FEC packets: where G is the constant GOP rate NPD and NBD are the numbers of transmitting P and B frames depending on Temporal Scaling level lTS NOSSDAV06
Video Quality - Overview • Two distortion factors • Frame Loss • Caused by Temporal Scaling and network packet loss • Appears jerky in the video playout • Measured by Playable Frame Rate • Quantization Distortion • Caused by a high quantization value with Quality Scaling • Appears visually as coarse granularity in every frame • Measured by ITS-VQM • Overall Quality • Distorted Playable Frame Rate [Wu+ 05 TOMCCAP] [Pinson+ 04] NOSSDAV06
Playable Frame Rate (R) • Frame Successful Transmission Probability • Where Frame Size • Frame Dependencies • Total Playable Frame Rate NOSSDAV06
Distorted Playable Frame Rate (RD ) • Quality scaling distortion varies exponentially with the quantization level • Distorted Playable Frame Rate [Frossard+ 01] NOSSDAV06
Algorithm • For each Repair and Scaling combination • Estimate video frame sizes (SI, SP, SB) • Compute streaming bitrate B and make sure it’s under capacity constraint T • Use frame sizes and FEC amount to get successfully frame transmission rate (qI, qP, qB) • Compute playable frame rate (R) • Estimate quality scaling distortion (D) • Compute distorted playable frame rate (RD) • Exhaustively search all FEC and Scaling combination and look for the optimal quality NOSSDAV06
Outline • Introduction • Model • Algorithm • Experiments • Conclusions NOSSDAV06
Methodology • Built a function RD() • Returns the distorted playable frame rate • Built an optimization program • TCP-Friendly Bitrate Constraint (T) • Searches repair and scaling levels for the highest RD • Compared three scaling choices with Adjusted FEC • Temporal Scaling • Quality Scaling • Temporal Scaling + Quality Scaling • Compared four FEC choices with the combination of Temporal Scaling and Quality Scaling • Non-FEC • Small Fixed FEC • Large Fixed FEC • Adjusted FEC NOSSDAV06
System Setting • GOP: IBBPBBPBBPBBPBB NOSSDAV06
Scaling Comparison with Adjusted FEC Low Motion High Motion NOSSDAV06
FEC Comparison with TS+QS NOSSDAV06
Conclusions • Summary • Derives analytical models for streaming video with Temporal plus Quality Scaling and FEC • Uses OR algorithm to optimize the quality • Compares scaling methods and FEC methods • Conclusions • Quality Scaling is more effective than Temporal Scaling • But when bandwidth is low and network loss is high, Quality Scaling should be used with Temporal Scaling • Motion matters • Adjusting FEC improves video streaming quality significantly • Better than fixed FEC and non-FEC NOSSDAV06
On Combining Temporal Scaling and Quality Scaling for Streaming MPEG Huahui Wu, Mark Claypool, Robert Kinicki Computer Science, Worcester Polytechnic Institute Questions?