Advances in Visual Computing: 6th International Symposium, ISVC 2010, Las Vegas, NV, USA, November 29-December 1, 2010, Proceedings, Part I (Lecture ... Vision, Pattern Recognition, and Graphics)

Front matter......Page 1
Introduction......Page 44
Low-Level Image Annotation......Page 45
Ontology-Driven Image Analysis......Page 47
Rules and Reasoning......Page 48
Results and Discussion......Page 52
References......Page 54
Introduction......Page 56
Component-Trees......Page 57
Learning Process......Page 58
Segmentation Process......Page 59
PC-MRA Segmentation......Page 60
Results......Page 62
References......Page 64
Introduction......Page 66
Data Description......Page 67
Manual Segmentation Procedure......Page 68
Comparison of Hand-Selected Data Sets......Page 69
Selection of Reference Data for Segmentation Comparison......Page 70
Comparison of Individual Cell Masks......Page 73
Conclusions......Page 75
References......Page 76
Introduction......Page 78
Methodology......Page 79
Algorithm Details......Page 80
Mathematical Properties of the Problem Formulation......Page 83
Results......Page 84
Conclusions......Page 86
References......Page 87
Introduction......Page 88
Intensity Blending on Image Boundaries......Page 90
Graph Reconstruction of Dendrite Networks......Page 91
Quantitative Representation of Single Spine Profile and Its Classification......Page 92
Experimental Results......Page 94
Conclusion and Future Works......Page 95
References......Page 96
Introduction......Page 97
Semi-uniform, 2-Different Tessellation......Page 99
Edge Tessellation Factors for the 2-Different Case......Page 100
Adaptive Tessellation Pattern with 2-Different Factors......Page 101
Results......Page 103
References......Page 105
Introduction......Page 107
Metric for Vertex Selection......Page 108
Metric for Half-Edge Collapse......Page 109
Two Phase Simplification Algorithm......Page 110
Results and Discussion......Page 111
Conclusion......Page 115
References......Page 116
Introduction......Page 117
Related Work......Page 118
The Computational Model......Page 119
The Continuity Equation......Page 121
The Wave Equation......Page 122
Dispersion and Wave Number Spectra......Page 123
Initial Conditions......Page 124
Implementation......Page 125
References......Page 127
Introduction......Page 129
Color Modification......Page 131
Color Hatching Textures......Page 132
Adaptive Delaunay Triangulation......Page 133
Estimating Drawing Directions......Page 134
References......Page 137
Introduction......Page 139
Relative Work......Page 140
Basic Constraint......Page 141
Parameter Modification Method......Page 145
Synthetic Experiments......Page 146
Real Image......Page 148
Conclusion......Page 149
References......Page 150
Introduction......Page 151
Review of Previous Work......Page 152
System Overview......Page 153
Decomposition of Skeleton Voxels......Page 154
Decomposition of Object Voxels......Page 155
Identification of Base Part......Page 156
Adjustment of Decomposed Skeleton Voxels......Page 157
Experimental Results......Page 159
References......Page 162
Introduction......Page 163
Related Work......Page 164
Entity Detection......Page 165
Entries and Exits......Page 167
Entry/Exit Zone Reliability......Page 168
Entry/Exit Region Evaluation......Page 170
Semantic Scene Actions......Page 173
References......Page 174
Introduction......Page 175
Search Method......Page 176
Combined-Model......Page 178
Driver Monitoring and ID Smoothing......Page 179
Video Search Results......Page 180
Training the Eye-State Classifier......Page 181
Detecting Closed Eyes......Page 182
Discussion......Page 183
References......Page 184
Introduction......Page 186
Low-Level Image Features......Page 187
Modeling Feature Point Sets......Page 189
Parameter Estimation and Feature Selection......Page 191
IXMAS Data Results......Page 192
References......Page 194
Introduction......Page 196
Block Formation......Page 198
Social Entropy......Page 199
Experiments and Discussion......Page 201
References......Page 204
Introduction......Page 206
Methodology......Page 207
Posture Estimation......Page 208
Fuzzy-Based Estimation of Fall Confidence Values......Page 209
Combination with Learned Accumulated Hitmap......Page 210
Experiments......Page 212
Conclusions and Outlook......Page 214
References......Page 215
Introduction......Page 216
Related Work......Page 217
Local Contrast Concept......Page 218
On the Problem of Signs......Page 219
Colour Visualisation......Page 221
References......Page 223
Introduction......Page 224
Geometric Calibration......Page 225
Color Calibration......Page 226
Gamut Extension Algorithm......Page 228
Experiments......Page 229
References......Page 231
Introduction......Page 233
Our Proposed Shading Attenuation Method......Page 234
Pigmented Skin Lesion Segmentation in Color Images......Page 236
Face Segmentation in Color Images......Page 237
References......Page 241
Introduction......Page 242
Cone Transform......Page 243
Histogram Normalization......Page 244
Opponent Color Space......Page 245
AR Face Dataset......Page 246
Experiments: Descriptor-Based System......Page 247
ALOI......Page 249
Degradation of Performance under Normal Conditions......Page 250
Discussion......Page 251
Conclusion......Page 252
References......Page 253
Introduction......Page 254
Related Work......Page 255
Target Color Consistency......Page 256
Model Effectiveness and Chromatic Locality......Page 257
Specificity of Model Parameters to Color......Page 259
Realistic Scene Application......Page 261
Conclusions and Future Work......Page 262
References......Page 263
Introduction......Page 264
Joint LAB-Range Bilateral Filter......Page 265
Joint LAB-Range vs. Joint Hue-Range Bilateral Filter......Page 266
Complex Log-Polar Transform in CIELAB Color Space......Page 267
Cluster Separability in Complex Log-Polar Space......Page 268
PCA Matching to Time-Variant Blended Cluster......Page 270
Color Stealing by Time-Variant PCA Matching Matrix......Page 271
Experiments on Blue Rose Creation by Stealing Pansy Blue......Page 272
References......Page 273
Introduction and Related Works......Page 274
Perceptual Aliasing and Point Matching......Page 276
Improving ASIFT......Page 278
Experiments......Page 280
References......Page 284
Introduction......Page 286
Approach......Page 287
Feature Extraction in Multiple Scales......Page 288
Multiresolution Framework......Page 291
Accuracy......Page 292
References......Page 294
Introduction......Page 296
Pre-processing......Page 297
Feature Extraction......Page 298
Fingertip Detection for Categorization......Page 300
ASL Alphabets......Page 302
ASL Numbers......Page 303
Test Sequences......Page 304
Conclusion......Page 305
References......Page 306
Introduction......Page 307
The SIFT Detector......Page 309
Difference of Gaussians Function Model......Page 310
Optimization and Computational Complexity of the Approaches......Page 311
Data Construction......Page 312
Results......Page 313
References......Page 317
Introduction......Page 319
Linear Dimensionality Reduction......Page 320
Feature Selection......Page 321
One Transform Based LDR......Page 322
Benchmark Data Sets......Page 324
Method Comparison......Page 325
Conclusion......Page 327
References......Page 328
Introduction......Page 329
Adaboost by Freund and Schapire......Page 330
Framework by Viola and Jones......Page 331
Comprising of Symmetric Object Characteristics by Inserting Symmetry Features......Page 332
Modified Algorithm......Page 333
Experimental Results......Page 335
Conclusions......Page 337
References......Page 338
Introduction......Page 339
Related Work......Page 340
Occluding Contour Camera......Page 341
Postprocessing......Page 342
Feature Filtering Using Occluding Contours......Page 343
Experiments......Page 344
Real Dataset with Complicated Background......Page 345
Conclusions and Future Work......Page 347
References......Page 348
Introduction......Page 349
Information Visualization Methods......Page 350
2D Expansion of Volume Data......Page 351
2D Expansion Visualization Method of High-Dimensional Data......Page 352
2D Expansion of High-Dimensional Data......Page 353
Visualization of 3D Pressure Data......Page 354
Visualization of 5D Lattice Random Walk......Page 356
References......Page 357
Introduction......Page 359
Related Work......Page 360
The Model......Page 361
The Visualization Framework......Page 362
Overview......Page 363
Zoom and Filter......Page 364
Detailed View......Page 366
Results......Page 367
References......Page 369
Introduction......Page 371
Related Work......Page 372
Optimizing Correspondence between Tensors......Page 374
Locating Tensor Degeneracy......Page 375
Rotational Inconsistency Around Degenerate Points......Page 376
Results and Discussions......Page 378
Conclusion......Page 379
References......Page 380
Introduction......Page 381
Related Work......Page 382
Plotting Algorithm......Page 383
Additional Visual Features......Page 385
Study Method......Page 386
Study Results......Page 388
Application......Page 390
Conclusions......Page 391
References......Page 392
Introduction......Page 393
Ontology Data Description......Page 394
Related Work......Page 395
Visualizing Pseudo Ontology with Non-tree Edges......Page 397
Visualizing Pathway Ontology Dataset......Page 398
Mapping Experimental Values on Ontology......Page 399
Discussion......Page 401
References......Page 402
Introduction......Page 404
Spectrum Segmentation......Page 406
Experiments and Results......Page 408
Conclusion......Page 412
References......Page 413
The Level Set Method......Page 414
An Extended Marching Cubes Algorithm......Page 415
Selecting Modified Mesh Fragments......Page 416
Polygonising a Cell......Page 417
Level Set Image Segmentation......Page 418
Results and Discussion......Page 421
References......Page 423
Introduction......Page 424
Related Work......Page 425
Multiple Instance Learning......Page 426
Target Localization Algorithm......Page 428
Automatic Target Localization......Page 430
Auto-locking for Unique Target Detection......Page 431
Sufficiency of Learned Models for Tracking......Page 432
Comparison with Manual Initialization......Page 433
Summary and Future Work......Page 434
References......Page 435
Introduction......Page 436
Modeling Fuzzy Spatial Constraints......Page 437
Particle Filtering for Multi-object Tracking......Page 439
Partitioned Sampling (PS)......Page 440
Ranked Partitioned Sampling (RPS)......Page 442
People Tracking......Page 443
Ant Tracking......Page 444
Hand Tracking......Page 445
References......Page 446
Introduction......Page 448
Proposed Method......Page 449
Object Tracking......Page 451
Object Segmentation......Page 452
Experimental Results and Implementation Issues......Page 455
Summary......Page 458
References......Page 459
Introduction......Page 460
Estimation of Prior Models Using Phase Correlation......Page 462
Optical Flow Estimation Using Block-Matching......Page 463
Smooth Optical Flow Estimation Using EC-QMMFs......Page 464
Preliminary Results......Page 466
References......Page 468
Introduction......Page 470
The DFD Equations......Page 471
Velocity Field Modeling......Page 472
Global Optimization......Page 473
Motion-Compensated Processing......Page 474
Experiments......Page 475
Conclusion......Page 477
References......Page 478
Introduction......Page 480
Gradient-Based MCT for Optical Flow......Page 481
Parameter Optimization and Experimental Results......Page 484
Conclusion......Page 490
References......Page 491
Introduction......Page 492
Stereo Assisted Moving Object Detection......Page 493
Depth Assisted Object Tracking......Page 494
Video Tracking under Partial Occlusion......Page 495
New Object, Splitting and Severe Occlusion Handling......Page 497
Tracking under Partial Occlusion in Different Disparity Layers......Page 498
Tracking under Partial and Severe Occlusion......Page 499
Conclusion......Page 502
References......Page 503
Introduction......Page 504
Face Segmentation and Quality......Page 506
Information Content......Page 507
Results......Page 509
References......Page 511
Introduction......Page 512
Levenshtein Distance in Iris Recognition......Page 514
Normalization......Page 516
Experimental Results......Page 517
Does LD Enhance Iris Recognition Accuracy Compared to Traditional Minimum HD?......Page 518
Which Tradeoff Exists between the Maximum Number of Shifts, Time Complexity and Recognition Accuracy?......Page 519
Conclusion......Page 520
References......Page 521
Introduction......Page 522
Problem Statement......Page 523
The Algorithm......Page 524
Database Acquisition......Page 526
Results......Page 527
Conclusions......Page 529
References......Page 530
Introduction......Page 532
Footstep Signals......Page 533
Feature Extraction and Matching......Page 534
Database and Experimental Protocol......Page 536
Experimental Results......Page 537
Conclusions and Future Work......Page 539
References......Page 540
Introduction......Page 542
Banana Wavelets......Page 543
Ear Detection......Page 544
Results......Page 547
References......Page 550
Introduction......Page 552
Manifold Learning......Page 553
Sparse Representations......Page 555
Sparse Graphs......Page 556
Experimental Results......Page 557
References......Page 560
Introduction......Page 562
Face Image Representation......Page 563
Adaptive Graph Appearance Model......Page 564
Common Sub-graph and Super-graph......Page 566
Adaptive Matching and Recognition......Page 567
Experiments......Page 568
References......Page 570
Introduction......Page 572
Feature Matching Approach......Page 573
Gradient-Based Approach......Page 574
Spatial-Temporal Frequency Based Approach......Page 575
Numerical Phantom Simulations......Page 577
Real Images......Page 578
Conclusions......Page 579
References......Page 580
Introduction......Page 582
Visual Analysis Process......Page 583
Preliminaries on graphs......Page 584
Discrete Operators on Graphs......Page 585
Discrete Semi-supervised Clustering......Page 586
Principle......Page 587
Visualization of Mitotic Figures......Page 588
Conclusion......Page 590
References......Page 591
Introduction......Page 592
Data Description......Page 593
Extended Edge Neighborhood......Page 594
Quality Index and Edge Thickness Calculation......Page 595
Testing 40000 Cells......Page 596
Bivariate Similarity Index......Page 598
Results......Page 599
Conclusions and Future Work......Page 602
References......Page 603
Introduction......Page 604
Optical Flow Computation......Page 605
Numerical Examples......Page 607
Concluding Remarks......Page 611
References......Page 612
Introduction......Page 614
Image-Based Features Extraction......Page 615
Knowledge Extraction......Page 617
Evaluation......Page 621
Conclusion and Future Work......Page 622
References......Page 623
Introduction......Page 625
Related Work......Page 626
Approach......Page 629
Evaluation......Page 630
Results......Page 631
Conclusion......Page 633
References......Page 634
Introduction......Page 635
Approximation Algorithms for GSS......Page 637
Theoretical Performance......Page 638
Generators......Page 640
Experimental Performance......Page 641
References......Page 644
Introduction......Page 645
Irregularity Measure......Page 647
Experiment Design and Result......Page 651
References......Page 653
Introduction......Page 655
Local Frame Coordinate Construction......Page 657
Vector Field Construction......Page 658
Run Time Performance and Memory Requirement......Page 660
Comparison and Limitation......Page 661
Conclusion and Future Work......Page 662
References......Page 663
Introduction......Page 665
Outline......Page 666
Related Work......Page 667
Preprocessing......Page 668
Trading Space for (Rendering) Time......Page 669
Adjusting the Quality......Page 670
Results......Page 671
Adapting to the Memory Requirements......Page 672
Rendering Performance and Quality......Page 673
Conclusion......Page 675
References......Page 676
Introduction......Page 677
Manifold Harmonics......Page 678
Implementation Details......Page 679
Local Spectrum Estimation......Page 680
Defining Regions......Page 681
Mesh Registration......Page 682
Propagating Editing Operations......Page 683
References......Page 685
Introduction......Page 687
Related Work......Page 688
Markov Random Field-Based Clustering......Page 689
Implementation......Page 691
Experimental Results and Performance Analysis......Page 692
References......Page 695
Introduction......Page 697
Related Work......Page 699
3D Dominant Plane Extraction......Page 700
3D Viewpoint Invariant Features......Page 701
Performance Evaluations......Page 703
Wide Baseline Alignment......Page 705
References......Page 707
Introduction......Page 709
Related Work......Page 711
Sparse Correspondences......Page 712
Sub-pixel Matching and Slant......Page 713
Parameter Estimation......Page 714
Synthetic Results......Page 715
Benchmark Results......Page 716
Real Outdoor Results......Page 717
Conclusion......Page 718
References......Page 719
Introduction......Page 721
Reconstruction Using Jacobi Iterative Method......Page 722
Procedure of Synthetic Shape Reconstruction......Page 723
Reconstruction Using FT......Page 724
Experiments......Page 725
References......Page 730
Introduction......Page 731
Bundle Adjustment......Page 732
Dense Disparity Maps......Page 733
Photometric Reconstruction......Page 734
Shadow Map Computation......Page 735
Relief Map Computation......Page 736
Albedo Reconstruction......Page 737
Conclusions......Page 738
References......Page 739
Introduction......Page 741
Robust Super-Resolution Mosaicking......Page 743
Levenberg Marquardt Method......Page 744
Experimental Results for LM Method......Page 746
References......Page 748
Introduction......Page 750
Dye Transfer Model......Page 753
Graph Diffusion......Page 756
Results......Page 757
References......Page 760
Introduction and Related Work......Page 762
Selection Angle......Page 763
Pilot Study on PAM Angles......Page 764
Main Study: Methods......Page 765
Results......Page 767
Discussion......Page 769
Conclusion......Page 770
References......Page 771
Introduction......Page 772
Related Work......Page 773
Design......Page 775
Apparatus......Page 776
Procedure......Page 777
Results......Page 778
Discussion......Page 779
Conclusion......Page 780
References......Page 781
Introduction......Page 782
Joining Road with Terrain......Page 783
Automatic Bridges and Tunnels......Page 784
Banking......Page 785
Freeways......Page 786
Freeway Connector Ramps......Page 787
Conclusions......Page 792
References......Page 793
Introduction......Page 794
System Overview......Page 796
Recognition Process......Page 797
Constructing States Using an SOM......Page 798
Constructing Recognition Path......Page 799
Experiment and Discussion......Page 800
References......Page 801
Back matter......Page 803