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報告人:林祐沁 學生 指導教授:童曉儒 老師 March 2, 2009

報告人:林祐沁 學生 指導教授:童曉儒 老師 March 2, 2009. Wireless Video Surveillance Server Based on CDMA1x and H.264. Outline. Introduction System Structure H.264 Coding Implementing Video Qos Control Strategies In Wireless Environment Conclusions. Introduction.

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報告人:林祐沁 學生 指導教授:童曉儒 老師 March 2, 2009

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  1. 報告人:林祐沁 學生 指導教授:童曉儒 老師 March 2, 2009

  2. Wireless Video Surveillance Server Based on CDMA1x and H.264

  3. Outline • Introduction • System Structure • H.264 Coding Implementing • Video Qos Control Strategies In Wireless Environment • Conclusions

  4. Introduction • Increasing requirement for securing and network technology. • Video surveillance based on IP has developed. • Remote video surveillance: • Wire -> Wireless(CDMA1x) • This paper presents : • A realization scheme of wireless video surveillance server based on CDMA1x and H.264. • Discusses key technique and wireless video quality of service(QoS) control strategies.

  5. System Structure • embedded hardware platform and embedded Linux operation system. • H.264 video compression standard. • local-storage function, keep important information in breaking off. • GPS orientation function, orientation and track of the mobile surveillance platform. • some strategies, rate control, congestion control, error control.

  6. Video Qos Control Strategies In Wireless Environment(1/2) • Media stream requirement of network bandwidth, delay, jitter, packet loss rate. • There are two thoughts: • Make the network have the ability to guarantee QoS. • needs to reconstruct the core equipments • Improves the transmission quality by the control function of the terminal system. • don’t change the network existing

  7. Video Qos Control Strategies In Wireless Environment(2/2) • End-to-end media stream QoS control structure:

  8. Congestion Control of Wireless Video • The most equation-based congestion control algorithm is TCP Friendly Rate Control(TFRC). • packet loss is found, then reduce the transmit rate. • This assumption is tenable in Wire environment. • the bit error rate of the wired channel is very low.

  9. Congestion Control of Wireless Video • Adopts equation-based congestion control algorithm for wireless channel. • Uses Markov mode of two states:wireless channel and wired channe.

  10. Rate Control of Wireless Video • Congestion control mechanism requires the transmit terminal adjust the transmit rate. • rate control recede the quality of media. • size of the picture, distortion, frame rate

  11. Rate Control of Wireless Video • The typical way is to control the bit number of coding output by adjusting the filling of coding buffer.

  12. Error Control of Wireless Video • wireless channel has high bit error rate. • Error-toleration and correction • video communication has a strict requirement for delay • The common data service reliable protocol (such as TCP). - FEC adds redundancy information to make get back correct.

  13. Error Control of Wireless Video • This paper not only uses FEC but also adopts delay-bound retransmission. • If ,requests transmitter to retransmit N • Tc:the present time. • RTT:estimate trip time. • Ds:time of tolerate estimate error, response of transmitter and decoding delay of receiver. • Td(N) is the deadline of packet arriving.

  14. Performance Analysis

  15. Advanced wireless Multiuser Video Streaming Using The Scalable Video Coding Extensions Of H.264/Mpeg4-avc

  16. Outline • Introduction • Scalable Video Coding And Media Adaptation • Radio Link Buffer Management For Scalable Video Streams • Simulation And Results • Conclusion

  17. Introduction • Wireless video streaming services, the need for higher capacity radio access networks. • One possible approach is the definition of quality-of-service (QoS) attributes for each media flow. • admission control • resource reservation

  18. Introduction • This paper presents : • Dynamic sharing of the resources by SVC. • Appropriate radio link buffer managementfor multiuser streaming services.

  19. Scalable Video Coding AndMedia Adaptation • Scalable Video Coding (SVC) • An extension of H.264/MPEG4-AVC. • Scalability function allows removal of parts of the bitstream. • Reduced temporal, SNR, or spatial resolution. • Bitstream consists of a base layer and one or several enhancement layers.

  20. Scalable Video Coding • Temporal scalability • often based on a temporal decomposition using hierarchical B pictures.

  21. Scalable Video Coding • Spatial scalability • motion-compensated prediction (MCP) structures for each layer. • achieved different encoder quality:QCIF, CIF, and 4CIF • SNR scalability • progressive refinement (PR) coding. • contains refinements for the residual (texture) data.

  22. Adaptation and Transport of SVC • hierarchical B pictures and the PR coding approach are combined. • The priority scale is starting from the lowest temporal layer. • PR fragments is next lower importance

  23. Adaptation and Transport of SVC • Rate adaptation dropping order • Drop PR fragments of the highest temporal level present. • Drop base layer of highest temporal level present.

  24. SVC NAL Unit header • Extension of the H.264/MPEG4-AVC NAL unit. • Byte 1:Forbidden Field(F), NAL Unit Reference Indicator(NRI), NAL Unit Type. • Byte 2:signals Simple Priority ID, discardable flag (D), Extended Bit (E). • Byte 3:Temporal,Spatial, and Quality Level.

  25. Priority Labeling • H.264/MPEG4-AVC only offer temporal scalability. • SVC bitstreams offer a wide range of options for rate adaptation. • Define the following intermediate priority value

  26. Priority Labeling • Existing solutions for temporal scalability, • Final priority value for each packet is defined

  27. Radio Link Buffer Management For Scalable Video Streams • Wireless Multiuser Streaming Environment • M users in the coverage area. • NAL units encapsulated in RTP packets. • Drop Strategy • If there are still packets which contain PR fragments(i.e. with pr <=254) in the buffer. • base layer fragments with no further dependencies (i.e. with pr = 255) • base layer fragments (i.e. with pr > 254)

  28. Simulation And Results

  29. Simulation And Results

  30. Simulation And Results

  31. Simulation And Results

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