Video Content Adaptation Based on SVC and Associated RTP Packet Loss Detection and Signaling

Author(s):  
Daniele Renzi ◽  
Peter Amon ◽  
Stefano Battista
Author(s):  
Francisco de Asís López-Fuentes

P2P video streaming combining SVC and MDC In this paper we propose and evaluate a combined SVC-MDC (Scalable Video Coding & Multiple Description Video Coding) video coding scheme for Peer-to-Peer (P2P) video multicast. The proposed scheme is based on a full cooperation established between the peer sites, which contribute their upload capacity during video distribution. The source site splits the video content into many small blocks and assigns each block to a single peer for redistribution. Our solution is implemented in a fully meshed P2P network in which peers are connected to each other via UDP (User Datagram Protocol) links. The video content is encoded by using the Scalable Video Coding (SVC) method. We present a flow control mechanism that allows us to optimize dynamically the overall throughput and to automatically adjust video quality for each peer. Thus, peers with different upload capacity receive different video quality. We also combine the SVC method with Multiple Description Coding (MDC) to alleviate the packet loss problem. We implemented and tested this approach in the PlanetLab infrastructure. The obtained results show that our solution achieves good performance and remarkable video quality in the presence of packet loss.


Author(s):  
Muhammad Hanif Jofri ◽  
Muharman Lubis ◽  
Mohd Farhan Md Fudzee ◽  
Shahreen Kasim ◽  
Mohd Norasri Ismail ◽  
...  

Author(s):  
Hermann Hellwagner ◽  
Ingo Kofler ◽  
Michael Eberhard ◽  
Robert Kuschnig ◽  
Michael Ransburg ◽  
...  

This chapter covers the topic of making use of scalable video content in streaming frameworks and applications. Specifically, the recent standard H.264/SVC, i.e., the scalable extension of the widely used H.264/AVC coding scheme, and its deployment for adaptive streaming, the combined activities of content adaptation and streaming, are considered. H.264/SVC is regarded as a promising candidate to enable applications to cope with bandwidth variations in networks and heterogeneous usage environments, mainly diverse end device capabilities and constraints. The relevant coding and transport principles of H.264/SVC are reviewed first. Subsequently, a general overview of H.264/SVC applications is given. The chapter then focuses on presenting architectural/implementation options and applications of H.264/SVC for adaptive streaming, emphasizing the aspect of where, i.e., on which network node and on which layer in the networking stack, in the video delivery path the content adaptation can take place; also, methods of content adaptation are covered. This pragmatic perspective is seen as complementing more general discussions of scalable video adaptation issues in the existing literature.


2013 ◽  
Vol 846-847 ◽  
pp. 1024-1030
Author(s):  
Li Li Wu ◽  
Chun Yan Yu

This paper focuses on the video distortion which is caused by the packet loss. Considering the relationship between the human visual perception which is caused by the packet loss and the visual characteristic of the video content, we present a no-reference model for video quality assessment based on Support Vector Machine. The feature vector of the SVM contain temporal complexity, spatial complexity, the average number of bits per frame and the packet loss rate. Temporal complexity, spatial complexity and the average number of bits per frame represent the visual characteristic of the video content. The value of the packet loss rate means the distortion which is caused by the packet loss intuitively. Experimental results show that this model has a good consistency with the subjective.


2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Jiarun Song ◽  
Fuzheng Yang

Packet loss will make severe errors due to the corruption of related video data. For most video streams, because the predictive coding structures are employed, the transmission errors in one frame will not only cause decoding failure of itself at the receiver side, but also propagate to its subsequent frames along the motion prediction path, which will bring a significant degradation of end-to-end video quality. To quantify the effects of packet loss on video quality, a no-reference objective quality assessment model is presented in this paper. Considering the fact that the degradation of video quality significantly relies on the video content, the temporal complexity is estimated to reflect the varying characteristic of video content, using the macroblocks with different motion activities in each frame. Then, the quality of the frame affected by the reference frame loss, by error propagation, or by both of them is evaluated, respectively. Utilizing a two-level temporal pooling scheme, the video quality is finally obtained. Extensive experimental results show that the video quality estimated by the proposed method matches well with the subjective quality.


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