Advances in Multimedia Information Processing - PCM 2010: 11th Pacific Rim Conference on Multimedia, Shanghai, China, September 2010, Proceedings, Part II

Cover......Page 1
Lecture Notes in Computer Science 6298......Page 2
Advances in Multimedia Information Processing -- PCM 2010, Part II: 11th Pacific Rim Conference on Multimedia, Shanghai, China, September 21-24, 2010 Proceedings......Page 3
Preface......Page 5
Table of Contents – Part II......Page 10
Table of Contents – Part I......Page 16
Introduction......Page 22
Principal Components Analysis......Page 23
Nonlinear Methods for Dimensionality Reduction......Page 24
Low-Level Features Extraction......Page 25
Feature Reduction Using CUR Matrix Decomposition......Page 26
The Compact Feature Representation by Auto-encoder......Page 27
Experimental Setup......Page 29
Comparison of Different Dimensionality Reduction Methods......Page 30
Experiment Using Auto-encoder with Different Depth......Page 31
Reference......Page 32
Introduction......Page 34
Query Formulation......Page 36
Scalability Improvement - Indexing Structure Design for Fast Search......Page 38
Recommendation Systems......Page 39
Conclusion......Page 40
References......Page 41
Related Work......Page 43
Notation......Page 44
Sparse Logistic Regression......Page 45
Sparse Logistic Regression for Correlation Learning......Page 46
Evaluation Metrics......Page 48
References......Page 50
Introduction......Page 52
Related Work......Page 53
Problem Definition......Page 54
SMS......Page 56
Photograph......Page 58
Heterogeneous PLL Objects Clustering......Page 59
Activity Theme Relevancy Measurement......Page 60
The Project Kaleido Photo – A Prototype of Mobile PLL Objects Organization System......Page 61
References......Page 62
Introduction......Page 64
Overview......Page 65
Video Segmentation by Script Partition......Page 66
Affective Script Partition Analysis......Page 67
Affective Feature Extraction......Page 69
Experiments......Page 70
References......Page 71
Introduction......Page 73
Partition Based Storage Format......Page 75
DPCM-Based Variable Length Coding......Page 76
Joint Coding for Co-located and Last-line Data......Page 77
Whole Architecture......Page 79
Implementation Results......Page 80
References......Page 81
Introduction......Page 83
Architecture of AVS Video Encoder and Mode Decision......Page 84
Original Algorithm: All Modes Enabled Algorithm......Page 86
Optimal Algorithm: Mode Pre-selection Algorithm......Page 87
First Step: 4-Way Parallel Scanning for Run, Level and VLC Table......Page 88
Second Step: Connection and VLC Table Fix......Page 90
Coding Performance Comparison......Page 91
Simulation and Resources Evaluation......Page 92
References......Page 93
Introduction......Page 94
Time Complexity......Page 95
 Empirical Analysis on RDC......Page 97
AVS Encoding RDP Experiments......Page 100
References......Page 103
Introduction......Page 105
Research Background......Page 106
Encoding Framework......Page 108
Temporal Sampling......Page 110
I-Frame Coding: Vector Quantization......Page 111
B-Frame Coding: Interpolation and Residual Coding......Page 114
Experimental Results......Page 116
Statistics of CMU Mocap Data......Page 117
Performance Evaluation......Page 118
Conclusion and Future Work......Page 119
References......Page 120
Introduction......Page 121
The Framework of our Algorithm......Page 122
Textural-Classification-Based Coding......Page 124
Experiment and Discussion......Page 125
References......Page 130
Introduction......Page 132
Searching for Candidates......Page 135
Adaptive Transform......Page 137
Experiments......Page 138
Conclusion......Page 140
References......Page 141
Introduction......Page 142
Overview of the Mode Decision Process in SVC......Page 143
Overview of Spatiograms......Page 146
Study of Mode Distribution between H.264 Modes......Page 147
Study of Similarity Score against SVC Only Modes......Page 148
Computation of Adaptive Threshold for Various Mode Categories......Page 149
New Algorithm for SVC Inter Layer Prediction Modes......Page 150
Experiments and Results......Page 151
Results for Experiment 1......Page 152
Results of Experiment 2......Page 153
References......Page 154
Appendix 1......Page 156
Introduction......Page 157
Overview of Mode Decision in H.264 Scalable Video Coding......Page 158
MB Classification and Check......Page 159
Fast Intra Mode Selection Algorithm......Page 161
Experimental Results......Page 162
References......Page 164
Introduction......Page 166
Mode Classification Based on RD Cost Characteristics......Page 167
Early Skip Mode Detection......Page 169
Best Non-skip Mode Decision......Page 171
Experimental Results......Page 172
Conclusions......Page 175
References......Page 176
Introduction......Page 177
Multi-pass VBR Rate Control Algorithm......Page 178
First and Second Pass Encodings......Page 179
The Third Pass Encoding......Page 183
Experimental Results......Page 184
References......Page 186
Introduction......Page 188
Global Nonlinear Algorithms......Page 190
Sparsity Reconstruction Embedding......Page 191
Sparse Reconstruction......Page 192
Explanation and Analysis......Page 193
Experiment Setup......Page 195
Experiment Results......Page 197
Conclusion......Page 198
References......Page 199
Introduction......Page 200
Statistical Learning Approaches......Page 202
Feature Selection......Page 203
Training and Off-Line Pre-classification......Page 204
Proposed Statistical Learning Based H.264 Encoder......Page 205
Experimental Results......Page 206
References......Page 209
Introduction......Page 211
Spatial Scalable Video Coder Structure......Page 212
Rate and Distortion Models in SAQD-Domain......Page 213
Optimum Bit Allocation......Page 216
Quantization Step Determination......Page 218
Experimental Results and Analysis......Page 219
References......Page 220
Appendix A......Page 221
Appendix B......Page 222
Introduction......Page 223
3-D Pyramid Decomposition......Page 225
Spatio-temporal CSF......Page 226
Contrast Masking......Page 228
Saliency Masking......Page 229
Experimental Results......Page 230
References......Page 233
Introduction......Page 235
Framework Overview......Page 237
Point Set Denoising......Page 238
Resolution and Initial Parameter Estimation......Page 239
Gaussian Kernel and Convolution......Page 240
Subsampling Method......Page 241
Experimental Results and Analysis......Page 242
Experimental Results for Decimation......Page 243
References......Page 245
Introduction......Page 247
Wavelet-Based Eigentransformation......Page 248
Experiments......Page 251
References......Page 255
Introduction......Page 256
Spatial Scalability......Page 257
Real-Time Architecture for Inter-layer Prediction of H.264/SVC......Page 259
ILIP-UP Architecture......Page 260
ILRP-UP Architecture......Page 261
Simulation Results......Page 262
References......Page 264
Introduction......Page 266
DCT Domain Downsizing......Page 267
Implementation......Page 269
Experimental Results......Page 270
References......Page 271
Introduction......Page 273
Inter/Intra Mode Decision for H.264/AVC......Page 274
Statistical Analysis of H.264/AVC Downscaled Videos......Page 275
Efficient Inter/Intra Mode Decision for H.264/AVC Downscaled Videos......Page 277
Experimental Results......Page 280
Experimental Results......Page 283
References......Page 284
Introduction and Related Work......Page 285
The MB Classification Method......Page 286
Insight of MB Class Information in Shot Change Detection......Page 288
The Class-Based Shot Change Detection Algorithm......Page 289
Experimental Results......Page 290
Discussion and Extension......Page 293
Conclusion......Page 295
References......Page 296
Introduction......Page 297
Optimization on the Flow of Choosing Modes......Page 298
Optimization on Pixel Search Algorithm......Page 299
Implementation and Optimization based on DSP......Page 302
Performance......Page 303
References......Page 305
Introduction......Page 306
System Architecture......Page 307
Difference Detection Flow......Page 308
Implementation Complexity Analysis......Page 310
Encoder Adaptability......Page 311
Testing Conditions......Page 312
Testing Results......Page 314
References......Page 317
Introduction......Page 318
The Temporal Scalable Decoding Process Flow and System Architecture......Page 319
The Proposed Method in the P Frame-Skipping Process......Page 321
Experimental Result......Page 326
Conclusion......Page 328
References......Page 329
Introduction......Page 330
Layered Block Matching Super-Resolution......Page 331
Video Coding With LBM-SR......Page 333
The Performance of LBM-SR......Page 335
References......Page 339
Introduction......Page 340
Proposed Sampling-Aided MVC Scheme......Page 341
Merging and Detaching the Sampled Views......Page 342
Experimental Results......Page 343
References......Page 347
Introduction......Page 349
The Structure of the Proposed WZ-to-AVS Transcoder......Page 351
Side Information Generation......Page 352
Transcoding Strategy......Page 354
Rate-Distortion Performance......Page 356
Complexity Analysis......Page 358
References......Page 359
Introduction......Page 361
Motion Vector Coding......Page 362
Motion Vector Competition......Page 363
Distribution of Motion Vector Predictor......Page 365
Motion Vector Predictor Index Coding Using Phased-in Code......Page 366
Experimental Results and Analysis......Page 368
References......Page 370
Introduction......Page 371
Related Work......Page 372
The Proposed Method......Page 373
Image Segmentation......Page 374
Cost Function for Transmission Map Estimation......Page 375
Refinement of Transmission Map Using Soft Matting......Page 377
Recovering the Scene Radiance......Page 378
Experimental Results......Page 379
References......Page 381
Introduction......Page 383
Overview of the Anisotropic Diffusion......Page 384
Method Noise of Anisotropic Diffusion......Page 385
Anisotropic Diffusion Using the Non-local Algorithm......Page 386
Experimental Results......Page 389
References......Page 391
Introduction......Page 393
Redundant Macro-Block Texture-based Selective Boundary Matching Algorithm......Page 394
RMB Coding......Page 395
TSBMA......Page 397
Experiment Results......Page 399
Conclusion......Page 401
References......Page 402
Introduction......Page 403
System Description......Page 404
R-D Curve of Input Image with System Constraints......Page 405
Features of Optimal Solutions......Page 406
Relations of System Parameters, Optimization Objective, and System Constraints......Page 408
Description of Optimization Algorithm......Page 410
Algorithm Effectiveness......Page 411
Computational Complexity......Page 412
Reference......Page 413
Introduction......Page 415
Motion Vector Extrapolation with MV Candidate List......Page 417
Tentative Projection with Pixel-MV Distortion Estimation......Page 418
Bi-direction MV Retrieval Based Extension......Page 421
MV Selection......Page 422
Experimental Results......Page 423
References......Page 425
Introduction......Page 426
Related Work......Page 427
Sender Side......Page 429
Receiver Side......Page 433
Evaluation......Page 434
Discussion......Page 436
References......Page 437
Introduction......Page 439
Impact of $ igma_{R}$ for Packet Delay Performance and Transmission Distortion......Page 440
Multi-Hop Packet Delay Bound Violation Modeling......Page 441
Problem Description......Page 443
Construction of R-D Profile......Page 444
Performance Evaluation of the Proposed Model......Page 446
Performance Evaluation of Low-Pass R-D Control......Page 447
Conclusion......Page 449
References......Page 450
Introduction......Page 451
Edge-weighted Adaptive Filtering (EWAF)......Page 452
Edge Modified Based Image Zooming......Page 455
Subjective Visual Evaluation......Page 457
Conclusions......Page 458
References......Page 459
Introduction......Page 460
HMM Based Soccer Video Events Detection Approach......Page 461
Middle Level Semantics Classification......Page 462
Video Text Type Classification......Page 463
Event Boundary Detection and Observations Extraction......Page 464
Event Detection Using Enhanced HMMs......Page 465
Experimental Results and Discussions......Page 466
Event Detection Performance Evaluation......Page 467
Discussions on the Selection of Overall Observations and Hidden States......Page 469
References......Page 470
Introduction......Page 473
Alternate Flashing System......Page 474
Synthesis of Unlit Frames......Page 475
Combining Lit and Unlit Frames......Page 477
Object Segmentation......Page 478
Conclusions......Page 481
References......Page 482
Introduction......Page 483
Motion Attention Detection......Page 484
Static Attention Detection......Page 485
Visual Attention Region Detection......Page 486
Object Motion Trajectory Tracking......Page 487
Experiments......Page 488
Conclusion......Page 490
References......Page 491
Introduction......Page 492
Related Studies......Page 493
Human-Computer Collaboration Model......Page 494
Recognition Improvement Framework......Page 495
Information Feedback Algorithm......Page 496
System Overview......Page 497
(I) Recognition Algorithm......Page 498
(II) Detection of Unfavorable Situation......Page 499
Configurations......Page 500
Results and Discussions......Page 501
References......Page 503
Introduction......Page 504
The Proposed Tracking Algorithm......Page 506
Training Phase......Page 507
Tracking Phase......Page 509
Experiments......Page 510
Conclusion and Discussion......Page 513
References......Page 514
Introduction......Page 515
Related Work......Page 516
LDA-Based Method......Page 517
Gibbs Sampling for LDA......Page 518
Soft-Constraint Based LDA......Page 519
Online LDA......Page 521
Recommendation Quality......Page 522
Efficiency of Online System......Page 524
References......Page 525
Introduction......Page 527
Degraded Chinese Character Recognition......Page 529
Coarse Classification Based on K-Nearest Neighbor Classifier......Page 530
Fine Classification via Sparse Representation......Page 531
Evaluation on Low Resolution Images......Page 532
References......Page 534
Introduction......Page 536
Related Work and Proposed System......Page 537
Extracting Visual Features......Page 538
Graphical User Interface......Page 541
Experiments and Results......Page 544
Conclusions......Page 545
References......Page 546
Introduction......Page 547
The Shape Model......Page 548
The Proposed Method......Page 549
The First Stage......Page 550
The Second Stage......Page 554
Experimental Results......Page 555
Conclusion......Page 557
References......Page 558
Introduction......Page 559
Proposed Method......Page 560
Identifying the Active Joint Dimensions......Page 561
Calculating the Un-correlation Measure......Page 562
Computing the Non-smoothness Measure......Page 563
Experiments......Page 564
Conclusion and Future Work......Page 568
References......Page 569
Introduction......Page 570
Materials and Methods......Page 571
Experimental Results......Page 572
Conclusions......Page 578
References......Page 579
Introduction......Page 580
Collaborative Filtering......Page 581
Tag-Boosted CF via Tripartite Graph Random Walk......Page 582
Tag Expansion via Lasso Logistic Regression......Page 584
Tag Incorporation via Weighting Parameter......Page 585
Dataset......Page 586
Effects of Tag-Boosted CF......Page 587
Effects of Tag Expansion......Page 588
Reference......Page 590
Introduction......Page 592
Related Work......Page 593
Problem Statement and Our Facing Aging Model......Page 594
Geometric Affine Transformation for Face Warping......Page 595
Motion Vector Deduction......Page 596
Aging Skin Texture Synthesis by Sparse Representation......Page 597
Sparse Representation of Aging Face......Page 598
Aging Parameters Learning......Page 599
Aging Texture Synthesis Based on MRF......Page 600
Conclusion and Future Work......Page 601
References......Page 602
Introduction......Page 604
The Multimodal Interaction Paradigm......Page 606
Grouping Methods......Page 608
Scenario......Page 610
The System Network......Page 611
The Client......Page 613
References......Page 614
Introduction......Page 616
Goal of the Proposed MOs Detection......Page 617
Motion JPEG......Page 618
DCT-SPC......Page 619
Algorithm......Page 620
MOs Detection in Codestream Domain......Page 621
More Robust Detection......Page 622
Experimental Results......Page 623
Robust Detection Using Multiple DCT Blocks......Page 624
References......Page 627
Introduction......Page 628
Zero-Block Mode Decision for H.264/AVC......Page 629
Computation of Number of Zero-Blocks Using Prediction Motion Vectors......Page 631
Experimental Results......Page 634
References......Page 636
Introduction......Page 638
Curvelet Transform......Page 639
Facial Feature Point Selection......Page 640
Curvelet Subband Entropy......Page 641
Experiments and Results......Page 643
Experiments without Cross-Validation......Page 644
Experiments with Cross-Validation......Page 645
Conclusion and Scope for Future Work......Page 646
References......Page 649
Introduction......Page 650
The Limitation of Traditional Technique......Page 651
The Definition of Video Structured Description......Page 652
The Key Aspects of Video Structure Description......Page 653
Compared VSD with Traditional IVS......Page 654
Introduction of a Prototype System......Page 655
Discussion......Page 656
References......Page 657
Introduction......Page 658
CVD Color Space......Page 660
Key Color Remapping......Page 662
Experimental Results......Page 665
References......Page 667
Introduction......Page 669
Video Segmentation......Page 670
Text Localization......Page 671
Text Extraction......Page 673
Structure of the Arabic Scripts......Page 674
Pre-Processing......Page 675
Script Segmentation......Page 676
Classification......Page 677
Experimental Results......Page 678
References......Page 679
Introduction......Page 681
Related Research......Page 682
Moving Objects Detection......Page 683
Y-axis Offset Calculation......Page 685
Correction of X-axis Perspective Distortions......Page 687
Video Contents Integration......Page 688
Experiments and Discussions......Page 690
References......Page 691
Introduction......Page 693
Related Works......Page 694
Select Candidates for Facial Features......Page 696
Pairwise Facial Features......Page 697
Experimental Results......Page 698
Conclusions......Page 701
References......Page 702
Introduction......Page 703
Model-Based HRTF......Page 705
Image Method Based Reverberation......Page 706
Spectral Notch Filtering......Page 708
Proposed Sound Externalization Method......Page 709
Performance Evaluation......Page 711
References......Page 713
Introduction......Page 715
The Fractional Fourier Transform And The Two Dimensions Fractional Fourier Transform......Page 716
Facial Data Acquisition And Visual Feature Extraction......Page 718
Emotional State Classification And Premilinary Result......Page 720
References......Page 724
Introduction......Page 726
Related Work and Methodology......Page 728
Patient’s Component......Page 730
References......Page 734
Introduction......Page 737
Related Work......Page 738
Motion Coherence Based Spatiotemporal Interest Point Detector......Page 739
Gradient Based Descriptor......Page 741
Kernels......Page 742
Implementation......Page 743
Human Action Recognition......Page 744
Conclusion......Page 747
References......Page 748
Introduction......Page 749
Metric Learning......Page 750
Neighborhood Component Analysis......Page 751
Proposed Semi-supervised NCA......Page 752
Experiments and Discussions......Page 753
Conclusions......Page 755
References......Page 756
Introduction......Page 757
The And-Ridge and and-Valley Image......Page 758
Text Region Location......Page 760
Train a Character Classifier......Page 762
Component Grouping......Page 763
Experimental Results......Page 764
References......Page 766
Introduction......Page 768
Studio Setup......Page 769
Computational Model......Page 770
Experimental Results......Page 772
References......Page 774
Author Index......Page 776