口試投影片(詹智傑) Final
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口試投影片(詹智傑) Final Presentation Transcript

  • 1. 自適性串流架構下之視訊影像 品質最佳化設計與實作 指導教授:楊士萱 學生:詹智傑 Design and Implementation of Quality Optimization Strategy in Adaptive Streaming
  • 2. Outline • Introduction to MPEG-DASH • Related Works • Proposed State-based Strategy • Results and Future Works 2
  • 3. Outline • Introduction to MPEG-DASH • Related Works • Proposed State-based Strategy • Results and Future Works 3
  • 4. Introduction to MPEG-DASH • Dynamic Adaptive Streaming over HTTP – 由3GPP與MPEG一起訂定的自適性串流標準 – 屬於HTTP/TCP的串流協定 – 唯一的自適性串流標準 4
  • 5. Introduction to MPEG-DASH • Dynamic Adaptive Streaming over HTTP – 何謂自適性串流(Adaptive bit-rate streaming) • 依據環境與應用需求即時性的調整視訊串流之碼率 – 視訊之解析度(Resolution)與品質(Quality)需求 – 網路狀態與撥放延遲(playback delay) – 客戶端之暫存器使用效率(Video buffer) – 使用終端之計算能力與複雜度 • 目的是獲得更佳之使用經驗品質(Quality of Experience, QoE)與頻寬使用效率(Bandwidth efficiency) 5
  • 6. Introduction to MPEG-DASH • Dynamic Adaptive Streaming over HTTP – 使用HTTP/TCP (not RTSP/UDP)的優勢 • 多數使用終端支援HTTP 協定 • TCP能提供高可靠性(reliable)且有秩序的傳送(ordered transmission) 並且能避免NAT與防火牆之阻擋問題 • HTTP-based streaming能夠重複使用已建置之 HTTP servers與caches做資料內容(content delivery)的傳遞 • HTTP-based streaming將串流連線之控制權由Server端 移轉至Client端 6
  • 7. Introduction to MPEG-DASH • Dynamic Adaptive Streaming over HTTP – 世界上第一個也是唯一的International standard • Apple HTTP Live Streaming (Apple-HLS) • Microsoft Live Smooth Streaming (Microsoft-LSS) • Adobe Dynamic Streaming for Flash (ADOBE-DSF) • OPEN IPTV Forum: HTTP Adaptive Streaming • Dynamic Adaptive Streaming over HTTP (MPEG-DASH) • … 7 Draft International Standard : 2011 Jan International Standard : 2011 Nov ISO/IEC International Standard : 2012 April ISO/IEC Technical Corrigendum 1 : 2013 May
  • 8. Introduction to MPEG-DASH • 系統架構(System Architecture) 8 HTTP server DASH client Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Media Presentation Description (MPD) Control heuristics HTTP client MPD parser Segment parser Media player HTTP 1.1 視訊串流服務 之”目錄”資料模型 視訊串流服務 之”媒體”資料模型
  • 9. Introduction to MPEG-DASH • 資料模型(Data Model) – Media Presentation Description (MPD) • Descript the video segment’s information in xml ex: timing, codec, resolutions, bit-rate … etc. – Segments • The media data. • ex: mp4, m4s, mp3 … etc. 9
  • 10. Introduction to MPEG-DASH • 資料模型(Data Model) – Media Presentation Description (MPD) 10 Media presentation Description Period ID = 1, start=0 s Period ID = 2, start=100 s Period ID = 3, start=200 s Period ID = 2 start=100s Adaptation Set 0 Adaptation Set 1 Adaptation Set 2 Adaptation set 1 Representation 1 5Mbps Representation 2 2Mbps Representation 3 500kbps Representation 2 2 Mbytes Segments
  • 11. Introduction to MPEG-DASH • 系統流程圖(System Flowchart) 11 Process MPD HTTP Get MPD Measure Download Rate Select Representation Measure Download Rate HTTP Get Segment #1 HTTP Get Segment #2 #1 #2
  • 12. Introduction to MPEG-DASH • 客戶端系統流程圖(Client side system flowchart) 12 Main part of MPEG-DASH Segment buffer
  • 13. Major contribution of this thesis • 實際建置一個包含伺服器與客戶端之視訊串 流系統,並加入MPEG-DASH框架 • 我們採用emulation的形式,相較於simulation 能提供更真實、更有修改與加入環境參數彈 性的系統 • 我們探索視覺品質(visual quality)、網路頻寬 (network bandwidth)以及暫存器使用量(buffer usage)的關聯性,並提出一套自適性品質控 制以提升感知上的品質(perceived quality) 13
  • 14. Outline • Introduction of MPEG-DASH • Related Works – VLC Player MPEG-DASH rate-based Quality Strategy – Related Researches in MPEG-DASH • Proposed State-based Strategy • Results and Future Works 14
  • 15. VLC Player Rate-based Quality Strategy • 實作於VLC Player DASH plug-in中 • Main consider principle – 當暫存器容量低於預設 threshold,接收最低碼 率串流以加速暫存器容 量補充 15 < minimum buffer threshold > minimum buffer threshold NoneAt least one Algorithm start Initial MPD Manager Current Period Get current Bandwidth Check current Buffer capacity Set current bandwidth as zero Gather Representations with same resolution of the player Check the quantity of Representations in candidate set Find target Representation from every AdaptationSets Find target Representation from candidate set Algorithm end Stage one Stage two
  • 16. VLC Player Rate-based Quality Strategy • Advantage – 視訊片段緩衝器補充速度快 • Disadvantage – 串流初始狀態的品質等級低 – 易受到網路瓶頸而品質崩潰 16
  • 17. VLC Player Rate-based Quality Strategy • Advantage • Disadvantage – 串流初始狀態的品質等級低 – 易受到網路瓶頸而品質崩潰 17 Bottleneck
  • 18. Outline • Introduction of MPEG-DASH • Related Works – VLC Player MPEG-DASH rate-based Quality Strategy – Related Researches in MPEG-DASH • Proposed State-based Strategy • Results and Future Works 18
  • 19. Related Researches in MPEG-DASH • [23]以馬可夫鍊的方式對無線網路的頻寬變 化特性做分析與歸類,並提出找尋最佳視 訊品質的演算法。 • [25]探討如何使用可調式編碼(Scalable video coding)提升網路儲存空間的使用效率。 • [26]以代理伺服器(Proxy)的角度出發,以網 路管理的QoE機制來替客戶選擇最佳的視訊 品質。 19
  • 20. Related Researches in MPEG-DASH • 雖然過去兩年MPEG-DASH相關的投稿文獻 絡繹不絕,但多數的共通點都如[23][25]採 用純模擬(Simulation)或數學推導,無法於實 際網路中驗證。 • 故本論文除了提出一套MPEG-DASH的品質 調控機制,也將實作一套系統進行驗證。 20
  • 21. Outline • Introduction of MPEG-DASH • Related Works • Proposed State-based Strategy • Results and Future Works 21
  • 22. Proposed State-based Quality Strategy • 本論文提出之DASH品質調控機制分 two stage – First Stage:以下載MPD的網路資訊預測前幾個 Segment的最佳品質 – Second Stage:依照網路與視訊片段暫存器使用 率來預測下一個Segment的最佳品質 22
  • 23. Proposed State-based Quality Strategy • Flowchart of first stage – Case 1: • MPD檔中的第一個 Segment。 – Case 2: • 新Adaptation set的第一 個Segment的決策流程。 – Case 3: • 一般之Segment的決策流 程 23 Choise segment Start !First segment !First segment in MPD No 1 2 3 No Yes Yes Initial Get target RepresentationList Sort Representations RepresentationStream
  • 24. Proposed State-based Quality Strategy 24 1 Download Initialization Source URL Download first five segment by using MPD’s bitrates as ref. Compute and save five segment’s downloaded bitrates End 2 Download Initialization Source URL Choice target level according to pre-algorithm’s last five segments Compute and save segment’s downloaded bitrates End Download target level segments 3 Choice target level according to five pre-segments Download target level segments Compute and save segment’s downloaded bitrates End Case 1: Case 2: Case 3:
  • 25. Proposed State-based Quality Strategy • Finite state machine of second stage 25 State 1-1 State 2-3 State 2-2 State 2-1 Network Throughputs > Highest Representation Network Throughputs < Highest Representation Network Throughputs < 80% Representations Network Throughputs < 80% Representations Network Throughputs (Bps) Segment Buffer (%)0 Adaptation Set’s Representation (Level) Level n Level 1 Level 2 State 3-2 State 3-1 Level k Network Throughputs < Representations Level 2 Network Throughputs > Representations Level 2 Buffer Fill persentage > 30% Buffer Fill persentage > 30% 30% 50% Buffer Fill persentage > 50% Buffer Fill persentage > 50% Case One Case Two Case Three
  • 26. Outline • Introduction of MPEG-DASH • Related Works • Proposed State-based Strategy • Results and Future Works – Emulation Settings – Objective Evaluation – Subjective Evaluation 26
  • 27. Emulation Settings • 實驗前提 – 本論文探討“頻寬高於MPD所能提供的最低碼率 視訊片段”的情境 – 本論文實作的是On demand的視訊串流服務 – 本論文探討“Client有足夠計算能力解析MPD中 任一等級的串流” – 本論文假設碼率與PSNR的關係為已知,故不須 於解碼的同時檢測畫面品質。 27
  • 28. Emulation Settings • 測試平台 28 Client Server Name Asus PC Asus PC CPU Intel Core 2 Quad 2.67GHz Intel Core 2 Quad 2.67GHz Memory 4G DDRII 2G DDRII OS Windows 7 Ubuntu 12.04 Network Ethernet Ethernet
  • 29. Emulation Settings • 測試平台 29 HTTP Server Apache Server (on demand) Network Emulator Client PC Notebook HTTP Internet DASH-AVC/264 Encoder
  • 30. Emulation Settings • 所使用之開源式軟體 30 Open Source Software Operating System Linux Ubuntu 12.04 LTE Web HTTP Server Apache 2 Server Database MySQL Language Perl, Bash script Network Emulator Linux tc commands Network Monitor libpcap & winpcap Server Monitor Monitorix Client side libraries libdash, libcurl, libxml2, libav
  • 31. Emulation Settings • 測試序列 31 Parameter Value Length (min:sec) 09:46 Segment size (second/segment) 2 Numbers of Frames 14315 Video codec H.264/AVC Container MP4 & M4S Frame rate (fps) 25 fps GOP size (frame) 25 Resolution (pixel) 480 x 360
  • 32. Emulation Settings • 測試序列 32 Level Video bitrate Level Video bitrate 0 100 kbits/s 7 1300 kbits/s 1 200 kbits/s 8 1600 kbits/s 2 350 kbits/s 9 1900 kbits/s 3 500 kbits/s 10 2300 kbits/s 4 700 kbits/s 11 2800 kbits/s 5 900 kbits/s 12 3400 kbits/s 6 1100 kbits/s 13 4500 kbits/s
  • 33. Emulation Settings • 序列特性:品質等級與碼率關係 33 The lower the bit-rate is, the smaller the gap is.
  • 34. Emulation Settings • 網路模型 – 高品質穩態網路模型 • 網路頻寬維持於MPD最高品質等級之上 – 遞增型網路模型 • 網路頻寬由低頻寬以穩定之速率上升 – 遞減型網路模型 • 網路頻寬由高頻寬以穩定之速率下降 34
  • 35. Emulation Settings • 網路模型 35 0 1000 2000 3000 4000 5000 6000 7000 0 100 200 300 400 Bitrate(kbits/sec) Time(s) 最高品質穩態網路模型 遞增網路模型 遞減網路模型
  • 36. Outline • Introduction of MPEG-DASH • Related Works • Proposed State-based Strategy • Results and Future Works – Emulation Settings – Objective Evaluation – Subjective Evaluation 36
  • 37. Objective Evaluation • 頻寬使用效率分析 – 最高品質穩態網路模型 0 1000 2000 3000 4000 5000 6000 7000 0 10 20 30 40 50 60 Bitrate(kbit/sec) Time(sec) Bandwidth Throughput(VLC[31]) Throughput(Proposed) ChosenBitrate(VLC[31]) ChosenBitrate(Proposed) 37
  • 38. Objective Evaluation • 頻寬使用效率分析 – 最高品質穩態網路模型 0 1000 2000 3000 4000 5000 6000 7000 0 10 20 30 40 50 60 Bitrate(kbit/sec) Time(sec) Bandwidth Throughput(VLC[31]) Throughput(Proposed) ChosenBitrate(VLC[31]) ChosenBitrate(Proposed) 38 0 1 2 3 4 5 6 7 8 9 10 11 12 13 0 1000 2000 3000 4000 5000 6000 7000 0 10 20 30 40 50 60 Level(#) Bitrate(kbit/sec) Time(sec) Bandwidth Throughput(VLC[31]) Throughput(Proposed) ChosenLevel(VLC[31]) ChosenLevel(Proposed)
  • 39. Objective Evaluation • 頻寬使用效率分析 – 遞增網路模型 39
  • 40. Objective Evaluation • 頻寬使用效率分析 – 遞減網路模型 40
  • 41. Objective Evaluation • 頻寬使用效率分析 – 遞減網路模型 41
  • 42. Objective Evaluation • 使用者觀賞品質分析 – 最高品質穩態網路模型 42
  • 43. Objective Evaluation • 使用者觀賞品質分析 – 最高品質穩態網路模型 43 +4.02845 dB
  • 44. Objective Evaluation • 使用者觀賞品質分析 – 最高品質穩態網路模型 • Average PSNR 44 PSNRY PSNRU PSNRV Proposed 41.9227dB 47.8613 dB 49.9766 dB VLC[31] 41.4475 dB 47.4507 dB 49.5599 dB △PSNR +0.4752 dB +0.4106 dB +0.4167 dB
  • 45. Objective Evaluation • 使用者觀賞品質分析 – 遞增網路模型 45
  • 46. Objective Evaluation • 使用者觀賞品質分析 – 遞減網路模型 46
  • 47. Objective Evaluation • 使用者觀賞品質分析 – 遞減網路模型 47
  • 48. Objective Evaluation • 使用者觀賞品質分析 – 遞減網路模型 • Average PSNR 48 PSNRY PSNRU PSNRV Proposed 39.311 dB 47.814 dB 48.930 dB VLC[31] 38.728 dB 47.325 dB 48.449 dB △PSNR +0.583 dB +0.489 dB +0.481dB
  • 49. Objective Evaluation • 使用者觀賞品質分析 – 遞減網路模型 • Average PSNR (from 8000~12000 frame) 49 PSNRY PSNRU PSNRV Proposed 38.411 dB 44.065 dB 44.54 dB VLC[31] 36.93 dB 42.875 dB 43.325 dB △PSNR +1.481 dB +1.19 dB +1.215 dB 畫面數: 8000~12000張
  • 50. Outline • Introduction of MPEG-DASH • Related Works • Proposed State-based Strategy • Results and Future Works – Emulation Settings – Objective Evaluation – Subjective Evaluation 50
  • 51. Subjective Evaluation • 串流起始狀態 – 最高品質穩態網路模型 (frame 829) Proposed (36.160dB) VLC[31] (27.810dB) 51
  • 52. Subjective Evaluation • 串流起始狀態 – 遞增網路模型 (frame 279) Proposed (30.796dB) VLC[31] (27.837dB) 52
  • 53. Subjective Evaluation • 串流起始狀態 – 遞減網路模型 (frame 373) Proposed (35.063dB) VLC[31] (26.696dB) 53
  • 54. Subjective Evaluation • 串流起始狀態(Demo) – 最高品質穩態網路模型 Proposed VLC[31] 54
  • 55. Subjective Evaluation • 串流起始狀態(Demo) – 遞減網路模型 Proposed VLC[31] 55
  • 56. Subjective Evaluation • 遞減網路模型低視訊品質狀態 – frame 9872 Proposed (44.129dB) VLC[31] (27.555dB) 56
  • 57. Subjective Evaluation • 遞減網路模型低視訊品質狀態 – Demo Proposed VLC[31] 57
  • 58. Results and Future Works • 本論文實作一套包含伺服器與客戶端的自 適性串流系統。 • 本論文在客戶端提出一套視訊品質評估機 制。 • 整體PSNR相較於[31]提升約0.5dB;在初始 狀態上,也能達到約1dB到4dB的提升;而 在網路瓶頸時也有1dB的提升。 58
  • 59. Results and Future Works • 提升品質調控機制的準確度 • 擴充其他視訊編碼標準與其相關特性探討 • 切割自適性串流機制與實際解碼的框架, 以做為智慧型家庭、微型視訊共享機制的 系統雛形。 59
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