Dünaamiline kiiruse jaotamine interaktiivses mitmevaatelises video vaatevahetuse ennustamineses

In Interactive Multi-View Video (IMVV), the video has been captured by numbers of cameras positioned in array and transmitted those camera views to users. The user can interact with the transmitted video content by choosing viewpoints (views from different cameras in the array) with the expectation of minimum transmission delay while changing among various views. View switching delay is one of the primary concern that is dealt in this thesis work, where the contribution is to minimize the transmission delay of new view switch frame through a novel process of selection of the predicted view and compression considering the transmission efficiency. Mainly considered a realtime IMVV streaming, and the view switch is mapped as discrete Markov chain, where the transition probability is derived using Zipf distribution, which provides information regarding view switch prediction. To eliminate Round-Trip Time (RTT) transmission delay, Quantization Parameters (QP) are adaptively allocated to the remaining redundant transmitted frames to maintain view switching time minimum, trading off with the quality of the video till RTT time-span. The experimental results of the proposed method show superior performance on PSNR and view switching delay for better viewing quality over the existing methods

Optimal layered representation for adaptive interactive multiview video streaming

We consider an interactive multiview video streaming (IMVS) system where clients select their preferred viewpoint in a given navigation window. To provide high quality IMVS, many high quality views should be transmitted to the clients. However, this is not always possible due to the limited and heterogeneous capabilities of the clients. In this paper, we propose a novel adaptive IMVS solution based on a layered multiview representation where camera views are organized into layered subsets to match the different clients constraints. We formulate an optimization problem for the joint selection of the views subsets and their encoding rates. Then, we propose an optimal and a reduced computational complexity greedy algorithms, both based on dynamic-programming. Simulation results show the good performance of our novel algorithms compared to a baseline algorithm, proving that an effective IMVS adaptive solution should consider the scene content and the client capabilities and their preferences in navigation

In-Network View Synthesis for Interactive Multiview Video Systems

To enable Interactive multiview video systems with a minimum view-switching delay, multiple camera views are sent to the users, which are used as reference images to synthesize additional virtual views via depth-image-based rendering. In practice, bandwidth constraints may however restrict the number of reference views sent to clients per time unit, which may in turn limit the quality of the synthesized viewpoints. We argue that the reference view selection should ideally be performed close to the users, and we study the problem of in-network reference view synthesis such that the navigation quality is maximized at the clients. We consider a distributed cloud network architecture where data stored in a main cloud is delivered to end users with the help of cloudlets, i.e., resource-rich proxies close to the users. In order to satisfy last-hop bandwidth constraints from the cloudlet to the users, a cloudlet re-samples viewpoints of the 3D scene into a discrete set of views (combination of received camera views and virtual views synthesized) to be used as reference for the synthesis of additional virtual views at the client. This in-network synthesis leads to better viewpoint sampling given a bandwidth constraint compared to simple selection of camera views, but it may however carry a distortion penalty in the cloudlet-synthesized reference views. We therefore cast a new reference view selection problem where the best subset of views is defined as the one minimizing the distortion over a view navigation window defined by the user under some transmission bandwidth constraints. We show that the view selection problem is NP-hard, and propose an effective polynomial time algorithm using dynamic programming to solve the optimization problem. Simulation results finally confirm the performance gain offered by virtual view synthesis in the network

Layer-Aware Forward Error Correction for Mobile Broadcast of Layered Media

The bitstream structure of layered media formats such as scalable video coding (SVC) or multiview video coding (MVC) opens up new opportunities for their distribution in Mobile TV services. Features like graceful degradation or the support of the 3-D experience in a backwards-compatible way are enabled. The reason is that parts of the media stream are more important than others with each part itself providing a useful media representation. Typically, the decoding of some parts of the bitstream is only possible, if the corresponding more important parts are correctly received. Hence, unequal error protection (UEP) can be applied protecting important parts of the bitstream more strongly than others. Mobile broadcast systems typically apply forward error correction (FEC) on upper layers to cope with transmission errors, which the physical layer FEC cannot correct. Today's FEC solutions are optimized to transmit single layer video. The exploitation of the dependencies in layered media codecs for UEP using FEC is the subject of this paper. The presented scheme, which is called layer-aware FEC (LA-FEC), incorporates the dependencies of the layered video codec into the FEC code construction. A combinatorial analysis is derived to show the potential theoretical gain in terms of FEC decoding probability and video quality. Furthermore, the implementation of LA-FEC as an extension of the Raptor FEC and the related signaling are described. The performance of layer-aware Raptor code with SVC is shown by experimental results in a DVB-H environment showing significant improvements achieved by LA-FEC. © 2011 IEEE.Hellge, C.; Gómez Barquero, D.; Schierl, T.; Wiegand, T. (2011). Layer-Aware Forward Error Correction for Mobile Broadcast of Layered Media. IEEE Transactions on Multimedia. 13(3):551-562. doi:10.1109/TMM.2011.2129499S55156213