Reference Frame Optimization for Multiple-Path Video Streaming With Complexity Scaling

2007 ◽  
Vol 17 (6) ◽  
pp. 649-662 ◽  
Author(s):  
Gene Cheung ◽  
Wai-tian Tan ◽  
Connie Chan
2010 ◽  
Vol 6 (3) ◽  
pp. 259-280 ◽  
Author(s):  
N. Qadri ◽  
M. Altaf ◽  
M. Fleury ◽  
M. Ghanbari

Video communication within a Vehicular Ad Hoc Network (VANET) has the potential to be of considerable benefit in an urban emergency, as it allows emergency vehicles approaching the scene to better understand the nature of the emergency. However, the lack of centralized routing and network resource management within a VANET is an impediment to video streaming. To overcome these problems the paper pioneers source-coding techniques for VANET video streaming. The paper firstly investigates two practical multiple-path schemes, Video Redundancy Coding (VRC) and the H.264/AVC codec's redundant frames. The VRC scheme is reinforced by gradual decoder refresh to improve the delivered video quality. Evaluation shows that multiple-path 'redundant frames' achieves acceptable video quality at some destinations, whereas VRC is insufficient. The paper also demonstrates a third source coding scheme, single-path streaming with Flexible Macroblock Ordering, which is also capable of delivery of reasonable quality video. Therefore, video communication between vehicles is indeed shown to be feasible in an urban emergency if the suitable source coding techniques are selected.


2016 ◽  
Vol 2016 ◽  
pp. 1-11
Author(s):  
Hui-Seon Gang ◽  
Goo-Rak Kwon ◽  
Jae-Young Pyun

To provide high-quality video streaming services in a mobile communication network, a large bandwidth and reliable channel conditions are required. However, mobile communication services still encounter limited bandwidth and varying channel conditions. The streaming video system compresses video with motion estimation and compensation using multiple reference frames. The multiple reference frame structure can reduce the compressed bit rate of video; however, it can also cause significant error propagation when the video in the channel is damaged. Even though the streaming video system includes error-resilience tools to mitigate quality degradation, error propagation is inevitable because all errors can not be refreshed under the multiple reference frame structure. In this paper, a new network-aware error-resilient streaming video system is introduced. The proposed system can mitigate error propagation by controlling the number of reference frames based on channel status. The performance enhancement is demonstrated by comparing the proposed method to the conventional streaming system using static number of reference frames.


1975 ◽  
Vol 26 ◽  
pp. 341-380 ◽  
Author(s):  
R. J. Anderle ◽  
M. C. Tanenbaum

AbstractObservations of artificial earth satellites provide a means of establishing an.origin, orientation, scale and control points for a coordinate system. Neither existing data nor future data are likely to provide significant information on the .001 angle between the axis of angular momentum and axis of rotation. Existing data have provided data to about .01 accuracy on the pole position and to possibly a meter on the origin of the system and for control points. The longitude origin is essentially arbitrary. While these accuracies permit acquisition of useful data on tides and polar motion through dynamio analyses, they are inadequate for determination of crustal motion or significant improvement in polar motion. The limitations arise from gravity, drag and radiation forces on the satellites as well as from instrument errors. Improvements in laser equipment and the launch of the dense LAGEOS satellite in an orbit high enough to suppress significant gravity and drag errors will permit determination of crustal motion and more accurate, higher frequency, polar motion. However, the reference frame for the results is likely to be an average reference frame defined by the observing stations, resulting in significant corrections to be determined for effects of changes in station configuration and data losses.


2011 ◽  
Author(s):  
Mark Mills ◽  
Stefan Van Der Stigchel ◽  
Andrew Hollingworth ◽  
Michael D. Dodd

Author(s):  
M.Yu. Khovritchev ◽  
V. Robert ◽  
N.V. Narizhnaya ◽  
T.A. Vasilyeva ◽  
A.A. Apetyan ◽  
...  
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