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Encoding stored video for stremming applications ieee paper ppt
1.
2. Outline
Introduction
Background Study
Problem Statement
Contribution of Paper
Sliding-Window Encoding Scheme
DCT Coefficient Selection
Simulation Result
Conclusion
References
3. Introduction
Digital video applications have become increasingly popular.
There are several video standards established for different purposes.
e.g, MPEG-1, MPEG-2, H.263…
Delay is an important issue in real-time communication.
4. Background Study
Streaming video applications
Video sequences are
Encoded off-line
Stored in a server
Pre-load before playback
E.g, VOD
5. Problem Statement
Bit allocation and video quality
Minimum distortion under the rate constraint
6.
7. Sliding-Window Encoding Scheme
Use future frames to improve video quality.
Set window size W to encode video frame.
frames : i, i+1, …, i+W-1
let frame i be the current frame
This proposed encoder better than real-time’s for the
same bitrate.
8. Buffer-size and Pre-loading Time Requirement
Why need buffer?
Store the excess bit waiting to be decoded
e.g, bits of future frames
Why need pre-loading time?
The delay before playback
9. DCT Coefficient Selection
Quantize the DCT coefficients
rate-distortion sense and macroblock level.
quantizer step-sizes(Q) largely determine the rate-distortion tradeoff.
There are not optimal for all video sequences by
limited quantizer selections and
predetermined run-length codeword.
The encoder can adjust the quantized coefficient’s level.
a marginal distortion increase but
a significant bit-rate reduction.
10. Simulation Result
Different bitrates:
32, 64, and 128 kbits/s
Different types of video sequences:
large facial movement
head and shoulder
camera panning
Compare with TMN8
11.
12. CONCLUSION
Better video quality than TMN8 in high motion-activity frames and
scene-change frames.
Require more buffer size and pre-loading time than TMN8.
13. References
[1] Coding of moving pictures and associated audio for digital storage media at up to about 1.5
Mbit/s, ISO/IEC 11 172, Aug. 1993.
[2] Generic coding of moving pictures and associated audio information, ISO/IEC 13 818, 1995.
[3] Video coding for low bit rate communication, ITU-T Recommendation H.263, March 1996.
[4] G. Cote, B. Erol, M. Gallant, and F. Kossentini, “H.263+: Video coding at low bit rates,” IEEE Trans.
Circuits Syst. Video Technol., vol. 8, pp. 849–866, Nov. 1998.
[5] Test model 5, JTC1/SC29/WG11 coding of moving pictures and associated audio MPEG
96/1260, ISO-IEC/JTC1/SC29/WG11, Mar. 1996.
[6] Video codec test model, TMN8, ITU-T/SG15, Jun. 1997.
[7] Encoding Stored Video For Stremming Applications, IEEE Transactions On Circuits And Systems For
Video Technology, Vol. 11, No. 2, February 2001
Editor's Notes
Digital video applications have become increasingly popular in our daily life. Currently, there are several video standards established for different purposes, for example, MPEG-1 & MPEG-2 for multimedia applications, and H.263 for video-conferencing applications. All these standards use discrete cosine transform(DCT), motion compensation(MC)(which involves motion estimation and motion-compensated prediction), quantization and variable length coding(VLC) as the building blocks. A rate control scheme, which decides the quantization step-size and monitors the buffer fullness, is another important part of the video encoder and can greatly affect the video quality. Delay is an important issue in real-time communication. For example, a delay of a few seconds is not acceptable for video conferencing applications. The whole process of capturing video, encoding, transmission, and decoding needs to be done within the delay constraint in real-time communication applications.
Streaming multimedia allows the user to begin viewing video clips on our server, without first downloading entire file. In this paper, our focus in on the non-real time visual communication such as VOD, digital library & non-interactive distance learning. For these applications, video sequences are encoded in advance and stored in the server. Users may access the server over a constant bitrate channel, such as the PSTN or ISDN. Before the playback, part of the video bitstream is pre-loaded in the decoder buffer to ensure that every frame can be decoded at the scheduled time. Examples of the streaming video applications are video-on-demand, archived video news, and non-interactive distance learning.**Public Switched Telephone Network (PSTN) or Integrated Services Digital Network (ISDN)
1st one is Bit allocation and video quality. The question is how do we encode the video sequence such that the encoded video can achieve the highest quality? And 2nd one is how to minimize distortion under the rate constraint.
It uses future frames to improve video quality. It is a flow control technique which belongs to data link layer of the OSI model. It solve the problem of missing frames during data transmission.Now try to understand the concept of sliding window. Suppose we have window size equal to 4. So 4 frames can be send at once. If any frame is not received then –ve acknowledgement is sent to transmitter and that frame will be send again. The frames left to the window transmitted properly and frames in right of window are not transmitted yet.
A buffer contains data that is stored for a short amount of time, typically in the computer's memory (RAM). The purpose of a buffer is to hold data right before it is used. For example, when you download an audio or video file from the Internet, it may load the first 20% of it into a buffer and then begin to play. While the clip plays back, the computer continually downloads the rest of the clip and stores it in the buffer. So buffer increases efficiency. Preloading is allowed as long as the users can tolerate the pre loading delay before playback.
Quantization on DCT coefficients in a rate-distortion sense at the macroblock level, which can help improve the video quality. Quantizer step-sizes largely determine the rate-distortion tradeoff in the compressed video. Better performance can be achieved by adjusting the level of the quantized coefficients, which minimizes the distortion subject to the rate constraint. Instead of encoding the quantized coefficients faithfully (i.e., encoding every quantized coefficient with its original quantized value), the encoder can adjust the quantized coefficient’s levelwhich may result in a marginal distortion increase but with a significant bit-rate reduction.
Simulations have been performed at different bitrates (32, 64, and 128 kbits/s). Different types of video sequences are tested. Different types of video sequences are large facial movement, head and shoulder, etc. Buffer size and preloading time of proposed method is greater than TMN8 encoder. When we compare largest degraded frame than we see proposed method is much better.
In this table you can easily see the comparison between TMN8 and Proposed method.
Currently used MPEG-H which is used for 3-D video and H.264 which is used for video conferencing are based on this theory.
Currently used MPEG-H which is used for 3-D video and H.264 which is used for video conferencing are based on this theory.