臺灣博碩士論文加值系統

即時視訊串流通常使用線上(on-line)的前向糾錯機制 (Forward Error Correction; FEC)，來回復傳輸中的損失，且具有低延遲的特性，使得高感知視覺品質能夠得到保證。然而，在速率變動的傳輸通道中，傳送有不同重要性的影片資料，讓FEC分配方式更加複雜。尚且，在沒有事先得知影片流量的相關資訊下，線上的前向糾錯機制更難有效地使用可用的FEC頻寬。通常，最佳的FEC分配方式是建立在一個分析的模型上，並且以離線(off-line)的方式在計算。在這篇論文中，我們提出以預測視框 (frame) 大小為基礎的FEC方法，來擴展離線的分析模型，以達成即時的FEC分配。藉由一連串的影片視框大小的預測，以一個視框接著一個視框方式，經最佳化的FEC分析模型計算，以求得個別視框的FEC分配量。為了達到上述的結果，本研究提出一個貪心演算法，藉由每次新的視框到達時，持續地修改FEC分配量，來減少因預測視框大小誤差所產生的效能降低。再者，本研究中也設計一個傳輸速率控制機制，以確保每一個影片視框，可以滿足其播出時間的限制。模擬實驗結果顯示，本研究所提出以預測為基礎的FEC方法，可以減少額外的FEC處理延遲，並且可以幾乎達到，離線的FEC分析模型所得到的感知視覺品質。

Real-time video streaming applications typically use an on-line forward error correction (FEC) technique to recover transmission losses with a low delay overhead so that the high perceived visual quality can be ensured. However, transmitting the prioritized video data over variable-rate transmission channels complicates the FEC rate allocation process, and the on-line FEC is difficult to efficiently utilize the available FEC bandwidth without the prior information of video traffic. Generally, the optimal FEC configuration can be computed off-line based on an analytical model. In this paper, a prediction-based FEC scheme is proposed to achieve the real-time FEC allocation by extending the analytical FEC model with the frame size prediction technique. Optimal FEC calculation can be conducted for a series of predicted video frames to lead a frame-by-frame FEC rate allocation, resulting in a significantly reduced data buffering delay. A greedy algorithm is proposed to mitigate the performance effects of frame-size prediction errors by continuously revising the FEC configuration each time a new frame arrives. Moreover, a transmission rate control mechanism is proposed to ensure that each video frames satisfies its presentation deadline. The simulation results show that the proposed prediction-based FEC scheme can minimize the additional FEC processing delay while achieving virtually the same perceived video quality that can be obtained by the off-line FEC model.

摘要 I
ABSTRACT II
誌謝 III
CONTENTS IV
LIST OF TABLES VI
LIST OF FIGURES VII
CHAPTER 1 INTRODUCTION 1
1.1 INTRODUCTION 1
1.2 DISSERTATION CONTRIBUTIONS 6
1.3 ORGANIZATION OF THE DISSERTATION 7
CHAPTER 2 BACKGROUND 8
2.1 REED-SOLOMON CODE 8
2.2 H.264/AVC OVERVIEW 10
2.3 VIDEO FRAME CORRELATION 14
2.4 VIDEO TRAFFIC PREDICTOR 17
2.4.1 Model-based Predictor 17
2.4.2 NN-based Predictor 19
2.4.3 LMS-based Predictor 21
2.5 TCP FRIENDLY RATE CONTROL (TFRC) 25
2.6 TEMPORAL SCALING 26
CHAPTER 3 RELATED WORK 28
3.1 OFF-LINE FEC (WU’S FEC) 28
3.2 ON-LINE FEC (PREDICTION-BASED FEC) 34
CHAPTER 4 LINEAR PREDICTION-BASED FEC SCHEME 36
4.1 SCHEME OVERVIEW 36
4.2 NORMALIZED LEAST-MEAN-SQUARE PREDICTION 39
4.3 PREDICTED GOP AND FAST FEC ALLOCATION 41
4.4 TRANSMISSION RATE CONTROL 45
4.4.1 End-to-end frame delay estimation 45
4.4.2 Frame dropping priority 48
CHAPTER 5 SIMULATION RESULT 49
5.1 CHANNEL MODEL 49
5.2 PERFORMANCE EVALUATION 51
CHAPTER 6 CONCLUSION 62
REFERENCES 63

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