Brain-Inspired Information Technology

✍ Scribed by Akitoshi Hanazawa, Tsutom Miki, Keiichi Horio

• Publisher: Springer
• Year: 2010
• Tongue: English
• Leaves: 509
• Series: Studies in Computational Intelligence 266
• Edition: 1st Edition.
• Category: Library

✦ Synopsis

''Brain-inspired information technology'' is one of key concepts for the development of information technology in the next generation. Explosive progress of computer technology has been continuing based on a simple principle called ''if-then rule''. This means that the programmer of software have to direct every action of the computer programs in response to various inputs. There inherently is a limitation of complexity because we human have a limited capacity for managing complex systems. Actually, many bugs, mistakes of programming, exist in computer software, and it is quite difficult to extinguish them. The parts of computer programs where computer viruses attack are also a kind of programming mistakes, called security hole. Of course, human body or nervous system is not perfect. No creator or director, however, exists for us. The function of our brain is equipped by learning, self-organization, natural selection, and etc, resulting in adaptive and flexible information system. Brain-inspired information technology is aiming to realize such nature-made information processing system by using present computer system or specific hardware. To do so, researchers in various research fields are getting together to inspire each other and challenge cooperatively for the same goal.

✦ Table of Contents

Intelligent Multimedia Communication Techniques and Applications (2010) (ATTiCA)......Page 1
Preface......Page 6
Contents......Page 8
Rate Control and Error Resilience for Object-Based Video Coding......Page 10
Introduction......Page 11
The Object-Based Coding Approach......Page 12
Object-Based Rate Control......Page 17
Object-Based Rate Control Architecture......Page 20
Object-Based Rate Control Techniques......Page 22
Object-Based Rate Control Walkthrough......Page 34
Object-Based Error Resilience......Page 35
Object-Based Error Resilient Architecture......Page 36
Error Resilient Encoding......Page 38
Error Resilient Decoding and Concealment......Page 42
References......Page 56
Introduction......Page 60
Production......Page 61
Distribution......Page 62
Consumption......Page 64
Stereo Interleaving......Page 65
Depth-Based Formats......Page 67
Multiview Video Coding Standard......Page 69
Block-Based Coding Tools for Multiview Video......Page 76
Depth Compression Techniques......Page 78
References......Page 80
Block-Based Hybrid Coding Scheme......Page 83
History of Hybrid Coding......Page 85
H.263......Page 86
MPEG-2 Video......Page 87
MPEG-4 Visual......Page 88
History......Page 89
Video Coding Layer (VCL)......Page 90
Features for Network Transportation......Page 104
Profiles and Applications......Page 109
Scalable Video Coding (SVC)......Page 110
Multiview Video Coding (MVC)......Page 116
Introduction......Page 118
Highlights of AVS-Video......Page 119
Profile and Application......Page 124
High-Performance Video Coding (HVC)......Page 125
3D Video Coding in MPEG......Page 127
Reconfigurable Video Coding in MPEG......Page 129
References......Page 131
Introduction......Page 133
An Overview of the AVS Standard......Page 135
Intra Prediction......Page 136
Variable Block-Size Motion Compensation......Page 137
Multiple Reference Picture Motion Compensation......Page 138
Quarter-Pixel Interpolation......Page 139
Improved Direct Mode......Page 142
Symmetric Mode......Page 145
Transform and Quantization......Page 146
Entropy Coding......Page 150
Loop Filter......Page 156
Interlace Coding......Page 159
Error Resilience Tools......Page 160
Complexity Analyses and Performance Testing for AVS......Page 161
Encoder Complexity......Page 162
Decoder Complexity......Page 166
Performance Comparison......Page 171
References......Page 172
Background and Related Work in Multi-resolution Video Compression Systems......Page 175
Spatial Resolution Scaling......Page 177
Hierarchical Resolution Image Coding......Page 178
Hierarchical Resolution Video Coding......Page 179
Super-Resolution Video Compression......Page 181
Subsampled Residual Video Coding......Page 182
System Model and Algorithm......Page 183
Intra Macroblock Encoding......Page 184
Inter Macroblock Encoding......Page 186
RAMBVCS Experimental Results......Page 187
System Model and Algorithm......Page 192
MAHRVCS Experimental Results......Page 196
Conclusion......Page 200
References......Page 201
Introduction......Page 203
Tree-Based P2P Live Streaming Systems......Page 206
Mesh-Based P2P Live Streaming Systems......Page 209
P2P VoD Systems......Page 214
Buffer-Forwarding P2P VoD Systems......Page 215
Hybrid-Forwarding P2P VoD Systems......Page 217
Prefetching Schemes......Page 219
Future Research Directions......Page 221
References......Page 222
Introduction......Page 224
Background......Page 226
Formal Description......Page 228
Implementation Aspects......Page 229
Small World Property......Page 231
Increased Likelihood of Data Sharing......Page 234
Rate-Distortion Characteristics......Page 240
Receiver-Driven Packet Requests......Page 241
Download Rate Estimation and Peer Replacement......Page 246
Setup......Page 247
Influence of Urgency and Popularity Factors......Page 248
Resilience to Free-Riders......Page 250
Utility-Based Scheduling......Page 251
Advantages of Delay-Based Mesh Construction......Page 252
Related Work......Page 254
References......Page 256
Intelligent Video Network Engineering with Distributed Optimization: Two Case Studies......Page 259
Challenges of Multimedia Traffic......Page 260
Optimization in Network Resource Allocation......Page 261
Intelligent Network Engineering for IPTV and P2P Systems......Page 264
Introduction......Page 265
Video Adaptation and Traffic Shaping......Page 269
Content-Aware Distortion-Fair Video Streaming......Page 272
Frame Dropping for Max-Min Utility Fair Share......Page 276
Simulations......Page 279
CAF Summary......Page 282
Introduction......Page 283
System Model......Page 284
Successive Water-Filling (SWaF) Algorithm......Page 285
Numerical Results......Page 288
SWaF Summary......Page 290
Conclusion and Future Work......Page 291
References......Page 293
Introduction......Page 297
Fountain Codes......Page 299
Streaming Systems with Fountain Codes......Page 303
UEP and Rateless Codes......Page 305
In-Network Processing......Page 306
Practical Network Coding......Page 307
Network Coding in Multipath Media Streaming......Page 309
Prioritized Network Coding......Page 311
Streaming with Rateless Coding and Network Coding......Page 314
References......Page 319
Introduction......Page 323
Neighbor Selection Algorithms......Page 325
Segment Scheduling Algorithms......Page 327
Cache Management......Page 331
Content Searching Algorithm......Page 337
Network Coding in Peer-Assisted Streaming Systems......Page 340
Core Idea......Page 341
Analytical Study of the Basic Model......Page 342
Conclusion......Page 343
References......Page 344
Introduction......Page 347
Ray-Space Representation for 3d Visual Communication......Page 348
Video Capture......Page 352
Correction......Page 354
View Generation......Page 355
2D/3D Display......Page 356
Free Listening-Point Using Sound Wave Ray-Space......Page 358
Free Listening-Point Using Acoustic Transfer Function......Page 359
Integrated FTV System......Page 360
Ray Capture......Page 361
Ray Display......Page 362
International Standardization......Page 363
References......Page 368
Introduction......Page 372
YouTube Background......Page 374
Workload Measurement of New Generation Media Servers......Page 375
YouTube Crawler for Internal Measurement......Page 376
YouTube Crawler for External Measurement......Page 378
Video Category......Page 379
Video Length......Page 380
Video File Size and Video Bitrate......Page 382
Date Added – Uploading Trend......Page 383
Views - User Access Pattern......Page 384
Growth Trend and Active Life Span......Page 386
User Ratings and Comments, Friends and Upload......Page 389
Small-World Phenomenon......Page 391
The Small-World in YouTube Videos......Page 393
Overview......Page 394
The Category of External Links......Page 395
The Time the Videos Get Linked......Page 396
External Views over the Time......Page 397
Daily Views from External Links......Page 399
Further Discussions......Page 401
Implications on Proxy Caching and Storage Management......Page 402
Can Peer-to-Peer Save YouTube?......Page 403
Conclusion......Page 404
References......Page 405
CTTB Standard......Page 408
Technical Review of CTTB......Page 409
Applications of CTTB......Page 419
CMMB Standard......Page 422
Technical Review of CMMB......Page 423
Applications of CMMB......Page 426
References......Page 427
Introduction......Page 429
An Overview......Page 430
Layer-3 Router-Level Topology Inference......Page 432
Autonomous System Level Topology Inference......Page 436
Layer-2 Topology Inference......Page 439
Inferring a Virtual Topology by Network Tomography......Page 440
Topology-Aware Multimedia Streaming......Page 441
Improving Delivery Rate......Page 442
References......Page 443
Introduction......Page 446
System Overview......Page 448
Shifted 3-D SPIHT Algorithm......Page 449
Adaptive Error-Resilient Strategy......Page 450
Flexible MDC......Page 451
Spatial-Domain MAP Estimator......Page 453
Coefficient Estimator......Page 455
Projection onto Convex Sets......Page 457
Simulation Environment......Page 460
Selected Simulation Results and Discussions......Page 461
Observations......Page 464
Conclusions and Future Work......Page 465
References......Page 466
Online Interactive Gaming System: hMouse YUN:hMouse......Page 468
Robust Real-Time Head Tracking in a Loop......Page 471
Head Pose and Motion Estimation......Page 473
Virtual Mouse Control......Page 474
System Performance and Experiments......Page 475
Summary......Page 477
Humanoid Emotive Audiovisual Avatar heaa-tang08a......Page 479
3D Face Modeling......Page 481
The UIUC iFace System......Page 484
Facial Expression Synthesis......Page 485
Viseme Synthesis......Page 486
Emotional Text-to-Speech Synthesis......Page 488
Experimental Results......Page 492
3D Face/Head Tracking Based Video Compression Jilin:03......Page 493
Introduction......Page 494
The System Framework......Page 495
3D Model Based Face TrackingJTuthesis2007......Page 496
Embedding Synthesized Face in H.264 Codec......Page 500
Experiments......Page 501
Future Work......Page 504
References......Page 505
Author Index......Page 509