Encoding Stored Video for
Streaming Applications
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR
VIDEO TECHNOLOGY, VOL. 11, NO. 2, FEBRUARY 2001
I.-Ming Pao
Ming-Ting Sun
Outline
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Introduction
Method
Simulation Result
Conclusion
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…
Introduction
 Basic building blocks
Introduction
 Real-time Visual Communication
 delay sensitive
 processes need to be done in constraint time
 rate control scheme is not suitable
 Nonreal-time Visual Communication
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delay tolerable
pre-loaded time
decoder buffer
rate control scheme is suitable
Buffer and Pre-loading
Introduction
 Streaming video applications
 Video sequences are
 encoded off-line
 Stored in a server
 Pre-load before playback
 e.g, VOD
Problem
 Bit allocation and video quality
 Minimum distortion under the rate constraint
Introduction
 Contribution of this paper :
1. Propose a sliding-window rate-control scheme.
2. A quantized DCT coefficient selection scheme.
3. Improve video quality for video streaming.
Outline
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Introduction
Method
Simulation Result
Conclusion
Global View
 Generate encoded bitstream
 Sliding-window encoding scheme
 Consider the constraints
 buffer-size
 pre-loading time
 DCT coefficient selection
 Run-length coding
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[20].
[20] I.-M. Pao and M.-T. Sun, “A rate-control scheme for streaming video encoding,”in Proc.
32nd Asilomar Conf. Signals, Systems and Computers, vol. 2, Asilomar, CA, Nov. 1998, pp.
1616–1620.
Sliding-Window Encoding Scheme
 Bit allocation
 rate and distortion scheme[18]
 low distortion or high-rate case
 high distortion or low-rate case
[18] J. Ribas-Corbera and S. Lei, “Rate control in DCT video coding for low-delay video
communications,” IEEE Trans. Circuits Syst. Video Technol., vol. 9, pp. 172–185, Feb. 1999.
Sliding-Window Encoding Scheme
 Bit allocation
 mathematical modeling[18]
[18] J. Ribas-Corbera and S. Lei, “Rate control in DCT video coding for low-delay video
communications,” IEEE Trans. Circuits Syst. Video Technol., vol. 9, pp. 172–185, Feb. 1999.
Sliding-Window Encoding Scheme
 Target number of bits for encoding frame
R × time
Buffer-size and Pre-loading Time
Requirement
 Why need buffer ?
 store the excess bits waiting to be decoded
e.g, bits of future frames
 Why need pre-loading time?
 the delay before playback
Buffer-size and Pre-loading Time
Requirement
 Buffer variation expression :
Buffer Size G
B0
p0
Buffer-size and Pre-loading Time
Requirement
A. Finding decoder buffer size and pre-loading
time given a video bitstream
overflow
underflow
Buffer-size and Pre-loading Time
Requirement
B. Generating a video bitstream given decoder
buffer size and pre-loading time
 To prevent the buffer-underflow :
 To prevent the buffer-overflow :
Bit Allocation with Constraints
Step 0 : Initialization :
 initialize the bit-count regulator
.
Step 1 : Compute the Proposed Target Bits for
Frame :
 compute the ideal target number of bits for frame i
(i = 0, 1, 2, 3, ...).
 avoid the underflow and overflow constraints.
Bit Allocation with Constraints
Step 2 : Macroblock-Layer Rate-Control :
 distribute
to the macroblocks in the ith frame.
 find DCT coefficient selection for each macroblock.
 encode bitstream
Step 3 : Update Bit-Count Regulator :
 update regulator :
 if there are more frames to be encoded, go to Step 1,
or else stop.
DCT Coefficient Selection
 Quantize the DCT coefficients
 rate-distortion sense and macroblock level.
 quantizer step-sizes(Q) largely determine the ratedistortion tradeoff.
DCT Coefficient Selection
 Run-length coding with LAST
 (LAST, RUN, LEVEL)
(0, 4, 6)
bitstream
DCT Coefficient Selection
 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.
DCT Coefficient Selection
 This paper use Lagrange multiplier method for
rate-distortion optimization in
 selecting the quantization parameter (QP) and
 adjusting the quantized DCT coefficients (LEVEL).
 the best combination of QP and LEVELs will be the
lowest cost in the rate-distortion sense.
DCT Coefficient Selection
 Goal is to find the minimum distortion under
the rate constraint :
 for every 8 X 8 block
 the optimal QP for the macroblock
 the LEVEL for each coefficient
DCT Coefficient Selection
 The constrained problem converts to an
unconstrained problem through the Lagrange
multiplier λ (≥ 0).
 .
 the problem becomes the determination of the
LEVELs of the coefficients.
Better
Outline
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Introduction
Method
Simulation Result
Conclusion
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
Outline
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Introduction
Method
Simulation Result
Conclusion
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.