selected papers from icip 2004 presented by peter
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Selected Papers from ICIP 2004
Presented by Peter
Secure Media Streaming & Secure Adaptation for Non-scalable Video (Invited Paper)John G.Apostolopoulos
Hewlett-Packard Labs, Palo Alto, CA
Summary
Targets Adapting the media for the time-varying available
network bandwidth for non-scalable video Protect the security of the media
Media data is encrypted while R-D information is unencrypted
Each P-frame is encoded into one packet Some P-frame is more important than others
that give less distortion for when being dropped
Total Distortion
Left: Carphone, Foreman Right: MrthrDhtr, Salesman
Secure Adaptive Streaming using a Secure-Media Rate-Distortion Hint Track (SM-RDHT) SM-RDHT for untrusted
streaming server RD information
embedded in hint track Media itself is
encrypted
SM-RDHT
Secure Transcoding at a Mid-Network Node using Secure Scalable Packets H.264 video is packetized into secure
scalable packets Unencrypted packet headers provide R-D
information – the importance of each packet Mid-network transcoder can perform R-D
optimized adaptation across multiple packets of a single stream or across packets of multiple different strems
1 byte R-D information for each packet (one frame)
Secure Transcoding at a Mid-Network Node using Secure Scalable Packets
Comments
Packet size is limited to one frame that reduce the flexibility
Distortion highly depends on method of error concealment methods used at the decoder that is unknown at the streaming server and Mid-Network nodes
Discussions
Simple AVC-Based Codecs with Spatial Scalability
R. Lange, Ł. Błaszak and M. Domański
Poznań University of Tachnology, Poland
Summary
Spatial scalability for AVC-Based Codecs Base layer is fully AVC-compliant Prediction using the interpolation based layer
and previous frame of enhancement layer Improved motion vector encoding Codec complexity is comparable to the
complexity of a pair of codec used for simulcast coding of two layer
Proposed to the AVC standard
To Layers Structure
Improved Encoding of Motion Vectors in the Enhancement Layer Optimum motion vectors are used in both layers Previous proposals used motion vectors in the same
layer to predict the current MV Improved version includes up-scaled base layer MV
to predict current MV Prediction residuals are encoded using CABAC Directional prediction is used as AVC standard for
8x16 blocks
Improved results from MV Predcition
Prediction in the Enhancement Layer Two additional reference frames
Interpolated from decoded current base-layer frame
Average of latter and last temporal reference frame
Scalable coding is efficient if temporal prediction and base layer prediction are mixed with substantial prob. For each mode.
Edge-adaptive interpolation technique is used that improve the performance by 1dB
Experimental Results
Comments
The proposed scalable codec is not compliant with AVC
Only 2 layers are presented, Not Finegranularity scalable in spatial resolution
Coding efficiency improvement is small comparing to simulcast
Discussions
Mode Mapping Method for H.264/AVC Spatial Downscaling TranscodingP. Zhang, Y. Lu, Q. Huang and W. Gao
Chinese Academy of Science,
Microsoft Research Asia
Summary
Focused only on mode decision part Cascaded Pixel-Domain transcoder (CPDT) Mode mapping only for 16x16 predict mode for I
frames and 8x8 prediction mode for P frames Save about 50% time cost High correlation between the four modes of original
MB and the corresponding MB at half resolution Two modes are proposed:
Simple Mode (SimMap) Use motion vectors information (MapMV)
Simple Mode Mapping Method (SimMap) For I frames
If more than 1 MB use I4x4 mode => use I4x4 in downsized frame
Otherwise use I16x16 For P frames
If all MB are I16x16 => I16x16 If more than 1MB are intra mode => I4x4 If all are P16x16 or skip mode => P16x16,
otherwise P8x8 is selected 4 sub-modes are decided by direct mapping
Mode Mapping with Motion Vector (MapMV) For the SimMap, the P16x8 and P8x16 are
not utilized When P8x8 is selected from SimMap:
Compute the distance between all MVs If all distance < Th, => P16x16 If D(MV1, MV3) and D(MV2,MV4) <Th, => P16x8 If D(MV1, MV2) and D(MV3,MV4) <Th => P8x16 Else P8x8
Experimental Results
Comments
PSNR loss more than 2dB at low bit rate
Discussions
A New Rate Control Scheme for H.264 Video Coding
P. Yin and J. Boyce
Corporate Research, Thomson Inc. Princeton
Summary
A new constant bit rate control method based on TMN8
Use simple preprocessing to achieve the target bit rate
Better target bit rate, bit allocation, buffer management
Adoption of virtual frame skipping Frame level and MB level rate control Simulations show that the method meet the target
bitrate even for scene changes and scene transitions
Preprocessing Stage
Chicken and egg problem in RDO: Quantization parameter QP is needed for RDO such as
mode decision Residue signal is needed to determine the QP, i.e. mode
has to be decided to obtain the QP For I frames, residue signals are estimated using
original pixels For P frames, rate constrained 16x16, 1 reference
frame ME is performed to obtain the estimated residue
Average QP of previously coded picture is used the determine the
Frame-layer rate control
Determine the frame QPf
Use GOP layer rate control GOP length = 1s Constraint the number of bit allocated for GOP to
prevent buffer overflow Unused bits are distributed over several following
GOPs Allocate more target bits for P pictures at the
beginning of GOP for better references Virtual buffer level is used to prevent QP deceases
very quickly
MB-layer Rate Control
For I picture, a higher distortion is given to MBs with less detail
For P picture, a higher distortion is given to the MBs with more residue errors
Better perceptual quality is maintained for I picture and can be propagated to following P pictures
QP variation within a frame is limited to QPf
2
Virtual Frame Skipping
After a frame is encoded, if buffer level > 90% of total buffer, next frame is virtual skipped until buffer level is less than 90%
Virtual skipped is achieved by code every MB in P picture to skip mode
Increase the frame QP by 2 after a frame is skipped
Experimental Results
Comments
An implemented rate control system
Discussions
Video Encoder Complexity Reduction by Estimating Skip Mode Distortion
I. Richardson and Y. Zhao
The Robert Gordon University
Summary
Predicts MBs that are likely to be skipped by the encoder
By estimating the increase in distortion due not skipping
Complexity reduced as motion estimation, FDCT, quantization and VLC is skipped for a skipped MB
Macroblock Distortion and Skip Prediction SAE is used as distortion measure:
The difference between the SAEskip and SAEnoskip is used to determine whether a MB will be skipped ot not
SAEnoskip is not available at the encoder, estimated by SAEnoskip of previous frames
Experimental Results
Experimental Results
Experimental Results
Comments
Discussions
An Improved Rate-Quantization Model for Rate Control in Real-Time Video EncodingB. Xie and W. Zeng
PacketVideo Corporation, San Diego
University of Missouri-Columbia
Rate-Distortion Optimized Video Coding with Stopping Rules: Quality and Complexity
M. Moecke and R. Seara
Federal University of Santa Catarina
Adaptive Rate Control for H.264
Z.G. Li, F. Pan, K.P. Lim, X. Lin and S. Rahardja
Institute for Infocomm Research, Singapore
On Resizing Images in the DCT Domain
C.L. Salazar and T.D. Tran
The John Hopkins University
Resizing of Images in the DCT Space by Arbitrary Factors
J. Mukhopadhyay and S.K. Mitra
Indian Institute of Technology, India
University of California, Santa Barbara
Video Multicast Over Channels Based on Distributed Source CodingA. Majumdar and K. Ramchandran
University of California, Berkeley
Peer-to-Peer Multipoint Videoconferencing
M.R. Civanlar, Ö. Özkasap and T. Çelebi
Koç University, Turkey
Low-Complexity Rate-Distortion Optimized Video StreamingJ. Chakareski, J, Apostolopoulos and B. Girod
Hewlett-Packard Labs,
Stanford University
Rate-Distortion-Complexity Adaptive Video Compression and StreamingM. Schaar, D. Turaga and V. Akella
University of California, Davis
Sony Electronics, San Jose
A Compressed-domain Heterogeneous Video Transcoder
W.C. Siu, K.T. Fung and Y.L. Chan
The Hong Kong Polytechnic University
Rate-Distortion-Complexity Optimization of Fast Motion Estimation in H.264/MPEG4-AVCJ. Støttrup-Andersen, S. Forchhammer and S.M. Aghito
Milestone System, Denmark
Research Center COM, DTU Denmark
Summary
Optimizing integer motion estimation in real-time H.264 encoding with respect to the trade-off between rate-distortion and complexity
Enhanced implementation on fast EPZS Speed-up factor of 4 compared to EPZS at 1%
increase in rate (speed-up =2000 when comparing with FS)
Complexity is measured by the number of weighted search positions (4x4 block is weighted by1)