臺灣博碩士論文加值系統

近年來，許多串流服務廠商已開始提供 3D 影像內容給用戶，甚至出現多視角(Multi-View)的 3D 影像內容使用戶沉浸在更好的感官體驗。然而即便目前無線網路的傳輸速度持續增長，傳送多視角 3D 影像的所有視點仍會佔據大多數的頻寬。另外在無線區域網路內(Wireless Local Area Networks, WLANs)進行有效率的群播服務，能夠在頻寬的限制下，滿足多人的需求。不過如何在多台分享器(Access Point, AP)下對一群的異質用戶們進行群播服務也是一大挑戰。
在這篇研究中，我們欲解決無線區域網路內進行多視角 3D 影像群播服務的問題。我們透過基於深度圖像繪圖法(Depth Image Based Rendering, DIBR)技術，使用戶能藉由收到的臨近左右視角影像，合成自身訂閱的視角影像。因此在此問題中我們須決定用戶該連接的分享器，以及分享器該群播的視角影像，使能夠在頻寬限制下，最大化所有滿足訂閱需求的用戶數。我們對此問題提出一有效率的演算法，並經由模擬實驗結果，顯示我們的演算法能有效地考量到視角合成以及多個分享器選擇問題，達到滿足多數用戶的需求。

In recent years, many video service providers start to provide 3D video contents,moreover, there is a new service which is called multi-view 3D video arise. The multi-view 3D video provides multiple view point to be chosen, also, it offer better immersive experience than traditional single view 3D video to users. But, the transmission of all views in multi-view 3D video would require significantly bandwidth consumption. Another interesting and well developed technology is the Wireless Local Area Networks (WLANs) which could support efficient multicast service on streaming with the limited wireless bandwidth. However, multicast to a set of heterogeneous user over multiple wireless Access Points (APs) also been a complicated problem.
In this thesis, we wont to solve the multicast multi-view 3D video in WLANs problem. We exploit the Depth Image Based Rendering (DIBR) technology to synthesize the user subscribed view from nearby left and right views. Therefore, in this problem we need to decide the user to AP association and the view session to be multicast from each AP. And the aim of our problem is maximize the number of satisfied users with bandwidth constraint. We propose an efficiently algorithm to solve this problem, and the simulation results show that our algorithm could further consider the view thesis and the inter APs coordination, and effectively satisfy most user demands.

口試委員會審定書 i
致謝 ii
摘要 iii
Abstract iv
1 Introduction 1
2 Related Work 9
3 Methodology 11
3.1 Problem Formulation ......................... 11
3.1.1 Model without View Synthesis .............. 11
3.1.2 Model with Depth Image Based Rendering .... 14
3.1.3 Scalable Video Coding ..................... 17
3.1.4 Heterogeneous Users ....................... 20
3.2 Algorithm ................................... 23
3.2.1 Multi-View Allocation ..................... 24
3.2.2 Multi-View Allocation with Heterogeneous Users . 28
3.3 Complexity Analysis ......................... 30
3.3.1 Multi-View Allocation ..................... 31
3.3.2 Multi-View Allocation with Heterogeneous Users . 31
4 Evaluation 32
4.1 Simulation Scenario ......................... 32
4.2 Performance Study and Discussion ............ 35
4.2.1 User Satisfaction ......................... 35
4.2.2 Preference Distribution ................... 36
4.2.3 Quality Constraint in DIBR ................ 37
4.2.4 Opportunity Ratio ......................... 39
4.2.5 AP Density ................................ 40
4.2.6 Scalable Video Coding ..................... 41
4.2.7 Heterogeneous Users ....................... 42
5 Conclusiion 44
Bibliography 45

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