The three volume set LNCS 6453, LNCS 6454, and LNCS 6455 constitutes the refereed proceedings of the 6th International Symposium on Visual Computing, ISVC 2010, held in Las Vegas, NV, USA, in November/December 2010. The 93 revised full papers and 73 poster papers presented together with 44 full and 6 poster papers of 7 special tracks were carefully reviewed and selected from more than 300 submissions. The papers of part I (LNCS 6453) are organized in computational bioimaging, computer graphics, behavior detection and modeling, low-level color image processing, feature extraction and matching, visualization, motion and tracking, unconstrained biometrics: advances and trends, 3D mapping, modeling and surface reconstruction, and virtual reality. Part II (LNCS 6454) comprises topics such as calibration, pose estimation, and reconstruction, segmentation, stereo, registration, medical imaging, low cost virtual reality: expanding horizons, best practices in teaching visual computing, applications, and video analysis and event recognition. Part III (LNCS 6455) mainly contains papers of the poster session and concludes with contributions addressing visualization, as well as motion and tracking.
Author(s): Richard Boyle, Bahram Parvin, Darko Koracin, Ronald Chung, Hammoud, Muhammad Hussain, Kar-Han Tan, Roger Crawfis, Daniel Thalmann
Series: Lecture ... Vision, Pattern Recognition, and Graphics
Edition: 1st Edition.
Publisher: Springer
Year: 2011
Language: English
Pages: 797
Cover......Page 1
Lecture Notes in Computer Science 6454......Page 2
Advances in Visual Computing, Part II......Page 3
ISBN-13 9783642172731......Page 4
Preface......Page 6
Organization......Page 8
Table of Contents – Part II......Page 28
Introduction......Page 36
Related Work......Page 37
Estimation of VPs......Page 38
Calibration of Camera Pairs......Page 40
Experiments......Page 41
Conclusion......Page 44
References......Page 45
Introduction......Page 46
Distortion Model......Page 47
Estimating Distortion Parameters from Circular Arcs......Page 48
Estimating Distortion Parameters......Page 49
Robust Distortion Parameter Estimation Algorithm......Page 50
Experimental Evaluation......Page 51
References......Page 54
Introduction......Page 56
Problem Formulation......Page 57
Spline Curve Construction......Page 58
Algorithm Initialization......Page 59
Algorithm for Projective Reconstruction......Page 60
Synthetic Data......Page 61
Real Image Curves......Page 63
References......Page 64
Introduction......Page 66
Reflectance Property Modeling of the Finger Surface......Page 67
Calibration of Lighting Directions......Page 70
Correction of Lighting Field......Page 71
Experimental Results......Page 72
Conclusion and Future Work......Page 74
References......Page 75
Introduction......Page 76
Related Work......Page 77
Line Extraction......Page 78
Scale Space Analysis......Page 79
Feature Point Descriptor......Page 81
1D Homographies......Page 82
Experiments......Page 84
References......Page 86
Introduction......Page 88
Constraint Analysis Indices and ICP Pose Estimation......Page 90
Simulated Results for Spacecraft Structures......Page 92
Results for Cuboctahedron Scanned with Neptec’s TriDAR Scanner......Page 96
Conclusion......Page 97
References......Page 98
Introduction......Page 99
Background......Page 100
Region and Edge-Adaptive Sampling......Page 101
Directional Features......Page 103
Results......Page 106
Conclusion......Page 107
References......Page 108
Introduction......Page 110
Related Work......Page 111
Graph Representing the Skin Image......Page 112
Universal Seed......Page 113
Experiments......Page 114
Results......Page 115
Conclusion......Page 117
References......Page 118
Introduction......Page 120
Basics......Page 121
Concentration Inequalities Based on Variance......Page 122
From Gaussian to Poisson Bounds......Page 123
Measuring the Error......Page 124
Type I&II Errors......Page 125
The Segmentation Process......Page 126
Discussion and Comparison with Previous Works......Page 128
Experimental Results and Practical Improvements......Page 129
References......Page 130
Introduction......Page 132
Image Segmentation with Shape Priors......Page 134
Image Segmentation with Spectral Priors......Page 137
Results......Page 138
References......Page 140
Introduction......Page 142
Idea......Page 143
Generating the Curve Field......Page 145
The Curve Field Transform......Page 146
Results......Page 147
Discussion......Page 150
References......Page 151
Introduction......Page 152
Chan-Vese Model......Page 153
Region-Scalable Fitting Energy Model......Page 154
Split Bregman Method for Minimization of Region-Scalable Fitting Energy......Page 155
Implementation......Page 157
Results......Page 158
Conclusion......Page 161
References......Page 162
Introduction......Page 164
Related Work......Page 165
Initial Matching......Page 166
Unreliable Pixel Detection......Page 168
Experiments......Page 169
References......Page 172
Introduction......Page 174
Related Work......Page 175
Spherical Harmonics Lighting......Page 176
Shape Recovery from Multiple Images......Page 178
Shape Recovery from a Single Image......Page 179
Experiments......Page 182
References......Page 184
Introduction......Page 186
Pinhole Camera Model......Page 187
Distribution of Intersections of All Pairs of Converging Lines......Page 188
Detecting Altitudes of the TOVPs Triangle......Page 189
Constraints from Three Altitudes of the TOVPs Triangle......Page 190
Simultaneously Detecting Radial Coordinates of the TOVPs and Focal Length......Page 191
Experiments......Page 192
Conclusions......Page 194
References......Page 195
Introduction......Page 196
Detecting Junctions......Page 197
Epipolar Geometry......Page 198
Affine Transformation......Page 199
Point Correlation......Page 200
Patch Equation......Page 201
Experimental Results......Page 202
References......Page 204
Introduction......Page 205
Previous Work......Page 206
Proposed System......Page 207
Analysis of the Setup......Page 208
Depth Super Resolution......Page 210
3D Reconstruction......Page 212
More Results......Page 213
References......Page 214
Introduction......Page 217
Previous Work......Page 218
Multi-segmentations......Page 219
Randomized Voting Scheme......Page 220
Results......Page 221
References......Page 226
Introduction......Page 227
Overview of SPH......Page 228
Neighbor List Construction......Page 230
Adaptive Neighbor List Algorithm......Page 231
Results and Discussion......Page 233
Conclusion......Page 235
References......Page 236
Introduction......Page 237
Basic Data Structure......Page 238
Node Types......Page 239
Node Extensions......Page 240
Render Preparations......Page 241
Shadows......Page 242
Particles......Page 243
Virtual Production......Page 244
Space Robotics......Page 245
Conclusion......Page 246
References......Page 247
Related Work......Page 248
Deformable Heightfields......Page 249
Prismfields and Vertical Drilling......Page 250
Prismfield Framework and Horizontal Drilling......Page 251
Implementation......Page 252
Results......Page 253
Conclusion......Page 254
References......Page 255
Appendix A: Screenshots of the Four Test Data Sets......Page 256
Introduction......Page 257
Problem Formulation......Page 258
Database......Page 260
Comparison without Pairwise Constraints......Page 262
Comparison with Iterative Closest Point Algorithm......Page 263
References......Page 265
Introduction......Page 267
Related Work......Page 268
Proposed Solution......Page 269
Visual Analysis of Interaction......Page 271
Experimental Results......Page 272
References......Page 276
Introduction......Page 277
Meshless Deformation Model......Page 278
Optical Flow Based Registration......Page 280
Parameter Settings......Page 282
Analytic Fluids......Page 283
Cardiac MRI Sequence......Page 284
Conclusions......Page 285
References......Page 286
Introduction......Page 287
The Statement of the Problem......Page 288
Rotation......Page 289
Scale......Page 290
Translation......Page 291
Results and Discussions......Page 292
References......Page 295
Introduction......Page 297
Distance Functions and Nonrigid Registration......Page 299
Variational Chamfer-Matching Energy......Page 300
Meshless Deformation Model......Page 301
Blending Local Models into a Global Deformation Field......Page 302
Quasi-Newton Registration Algorithm......Page 303
Experiments......Page 304
References......Page 307
Introduction......Page 308
Lens Distortion Model......Page 309
Estimation of the Distortion Parameters......Page 310
Experimental Results......Page 315
References......Page 317
Introduction......Page 318
Disparity Initialization......Page 320
Sub-pixel Refinement......Page 321
Bundle Adjustment......Page 322
Robust Estimation......Page 323
Experimental Results......Page 324
References......Page 325
Introduction......Page 327
Prediction Framework......Page 329
Regression-Based Predictive Model......Page 331
Intra- vs. Inter-patient Prediction......Page 332
Comparative Analysis of Regression Methods......Page 333
Conclusion......Page 335
References......Page 336
Introduction......Page 337
GGVF......Page 338
Model Dynamics......Page 341
Quantitative Evaluation through a Ground Truth Model......Page 343
Qualitative Evaluation on Clinical Data......Page 344
Discussion and Conclusion......Page 345
References......Page 346
Introduction......Page 347
Related Work......Page 348
Preprocessing......Page 349
Cost Function......Page 350
Image Data and Independent Reference......Page 353
Results......Page 354
References......Page 355
Introduction......Page 357
Graph Cut Segmentation......Page 358
Symmetric Shape Prior Estimation......Page 360
Flux......Page 361
Definition of Piecewise Potential......Page 362
Synthetic Data Sets......Page 363
SBFSEM Image Stack......Page 364
Conclusion and Future Work......Page 365
References......Page 366
Introduction......Page 367
Laws of Optics......Page 368
The Image Ray Transform......Page 369
Refinements......Page 370
Extraction Technique......Page 372
Results......Page 373
Discussion and Future Work......Page 375
References......Page 376
Introduction......Page 377
Proposed Method......Page 378
Stage 1: Multi-layer Segmentation and Candidate Generation......Page 379
PCA Based Model Generation......Page 381
Results and Discussions......Page 383
References......Page 384
Introduction......Page 386
Related Work......Page 387
Low-Cost, Multi-touch, Multi-surface VR......Page 388
Vertical Surface......Page 389
Shadow Grab: A Representative Interface Technique......Page 390
Manipulating Objects in Front of Low Cost Displays......Page 391
Infrared Interference Reduction......Page 392
Conclusion......Page 393
References......Page 394
Introduction......Page 396
Demonstrated Usefulness of Immersive Environments......Page 397
Development of Low Cost Immersive Systems......Page 398
Hardware Recipes......Page 399
Software Systems......Page 401
Volume Visualization......Page 402
Training via World Walk-Through......Page 403
Development Experiences......Page 404
Conclusion......Page 406
References......Page 407
Introduction......Page 408
Interacting with DTI Models......Page 409
Brain Model Manipulation......Page 410
Selecting Tracts......Page 411
Gesture Recognition......Page 412
Results......Page 413
Accommodating User Workflow......Page 414
Conclusion......Page 415
References......Page 416
Introduction......Page 417
Design Goals and Constraints......Page 418
Display Management and Rendering......Page 419
Multi-modal Input and Haptic Feedback......Page 421
User Interfaces......Page 422
IMD Software Design......Page 423
Physical Realism and Technical Challenges......Page 424
Future Direction......Page 425
References......Page 427
Introduction......Page 429
Technology Development for Synchronous Collaboration......Page 431
Institutional Alignment......Page 432
Curriculum Alignment......Page 434
Student Participants and Team Structure......Page 436
Cross-Site Tool and Workflow Alignment......Page 437
Cross-Site File Sharing......Page 438
Conclusion and Future Work......Page 439
References......Page 440
Introduction......Page 441
Parson’s Programming Puzzles......Page 442
AutoTutor......Page 443
Process Visual Analyzer (ProVisZer)......Page 444
The Process Tree and Data Visualization of Student Interaction......Page 446
Conclusion......Page 449
References......Page 450
Introduction......Page 451
Laser Scanner Acquisition, Registration and Integration......Page 452
Validation......Page 454
Offsetting Object Boundary and 3D Printing......Page 456
Discussion and Experimental Results......Page 457
Conclusion......Page 460
References......Page 461
Introduction......Page 464
Related Work......Page 465
Teaching Concept......Page 466
Course Contents......Page 467
ARace......Page 468
AR Painting......Page 469
Supervision Effort and Supervisors' Experiences......Page 470
Students' Feedback......Page 471
References......Page 473
Introduction......Page 474
Light Reflection Principle......Page 475
Method......Page 477
Test and Result......Page 480
References......Page 482
Introduction......Page 484
Proposed Method......Page 485
Feature Extraction......Page 486
Learning and Retrieval......Page 488
Macro-grid Representation of Images......Page 490
Retrieval Evaluation......Page 491
Conclusion and Future Work......Page 492
References......Page 493
Introduction......Page 494
Related Work......Page 495
Parametric 3d Rope Model......Page 496
2d Image Synthesis......Page 497
Estimation of Rope Parameters......Page 498
Experimental Evaluation......Page 500
Conclusions and Outlook......Page 502
References......Page 503
Introduction......Page 504
Homography Estimation......Page 507
Cell Broadband Engine......Page 510
Optimization for One SPE......Page 511
Experimental Results......Page 512
Conclusion and Future Works......Page 514
References......Page 515
Introduction......Page 516
Related Work in Conceptual Query Expansion......Page 517
Concept Extraction Using Wikipedia......Page 518
Image Search Using Conceptual Query Expansion......Page 519
Hybrid Feature Vector Generation......Page 520
Image Organization Using Self-Organizing Map......Page 521
Experiment Results......Page 522
References......Page 524
Introduction......Page 526
State of the Art of Image Difference Metrics......Page 527
The New Metric......Page 528
Creating the Dataset......Page 529
Experimental Setup......Page 531
Experimental Results......Page 532
References......Page 534
Related Work......Page 536
Navigational Aids......Page 537
Screen Space Pointing Arrow......Page 538
Distance Based Illumination......Page 539
User Study......Page 540
References......Page 544
Introduction......Page 546
Related Work......Page 547
Shader Classification......Page 548
Indirect Shader......Page 549
Layer-Based Shader Synthesizer......Page 550
Interactive User-Controlled Shader Painting......Page 551
Volumetric Painting......Page 552
Experimental Results......Page 553
Conclusions and Future Work......Page 554
References......Page 555
Introduction......Page 557
The Data-Driven Framework......Page 559
Visualization of Patterns and Their Changes......Page 561
Measuring Result Quality of the Merge Algorithm......Page 563
Comparing Proposed Techniques with Uniform Time Axis......Page 565
References......Page 566
Introduction......Page 568
Polygonal Mesh Cutaway......Page 570
RibbonView......Page 571
Cutter Model Representation and Construction......Page 572
Cutaway Types Supported......Page 573
Context-Preserving Rendering Styles of the Cutaway Region......Page 574
Cutter Mesh Editing......Page 575
Experimental Results and Discussion......Page 576
Discussion......Page 577
References......Page 578
Introduction......Page 580
Conventional Visualisation and Visual Analytic Approaches......Page 581
Proposed Visual Analytics Model......Page 582
Vital Signs Visualisation......Page 584
Vital Signs Visualisation......Page 585
Conclusion......Page 586
References......Page 587
Introduction......Page 589
Main Idea......Page 590
Generation of an LOD-Hierarchy......Page 591
Efficiency for Real-Time Interaction......Page 592
Hierarchical Star Coordinates......Page 593
Interactive Queries for Real-Time Analysis......Page 594
Isolating Outliers......Page 595
Possible Drawbacks......Page 596
Conclusions and Possible Future Research......Page 597
References......Page 598
Introduction......Page 599
Biomechanical Motion Data......Page 600
Dimensionality Reduction......Page 601
Interactive Visual Analysis of Patterns in Motion Data......Page 603
Exploring the Motion Space......Page 604
Analyzing the Embedding Space......Page 605
Discussion......Page 606
References......Page 607
Introduction......Page 609
Proposed Methodology......Page 610
Preprocessing and Background Subtraction......Page 611
Feature Extraction......Page 612
Experimental Results......Page 615
References......Page 617
Introduction......Page 619
System Setup......Page 620
Architecture......Page 621
Volumetric Occupancy......Page 622
Person Localization and Tracking......Page 623
Textured Visual Hull......Page 624
Head Pose Estimation......Page 625
Computational Performance......Page 626
Pilot Applications......Page 627
Conclusions......Page 628
References......Page 629
Introduction and Related Work......Page 631
2-D Affine Image Registration......Page 632
Action Fragment......Page 633
MRF-Based Fragment Localization......Page 634
Fragment Models......Page 635
Action Classifier......Page 637
Results......Page 638
Conclusion......Page 639
References......Page 640
Introduction......Page 641
Radial Distance......Page 642
Locality Preserving Projections (LPP)......Page 644
Training......Page 646
Results......Page 647
References......Page 649
Introduction......Page 651
Focusing on Human Motion......Page 652
Online Classification of Action Primitives......Page 655
Actions: Learning and Imitation......Page 658
References......Page 661
Introduction......Page 663
Hand Detection in Complicate Scenario......Page 664
Motion Times Image Method for Hand Identification......Page 665
Description and Recognition of Hand Gestures......Page 667
Experimental Results......Page 668
Hand Detection in a Complicate Scenario......Page 669
Conclusion and Future Work......Page 670
References......Page 671
Introduction......Page 672
Proposed Method......Page 674
LFW Dataset......Page 676
The Negative Set......Page 677
Experimental Results......Page 679
References......Page 680
Introduction......Page 682
Graph Definitions and Operators on Weighted Graphs......Page 684
Eikonal Equation on Weighted Graphs......Page 685
Numericals Schemes and Algorithms......Page 686
Weighted Distances Computation on Graphs......Page 688
Image Processing......Page 689
References......Page 692
Introduction......Page 694
Conventional 3D-DCT Based Method......Page 695
Proposed Method......Page 696
Adaptive Scanning for 3D Block Construction......Page 697
Variable Size 3D Block Construction......Page 698
The Proposed Method Based on Adaptive 3D Block Construction......Page 699
Experimental Results......Page 700
References......Page 703
Introduction......Page 704
Plant Texture Extraction......Page 705
Gabor Filters......Page 706
Texture Analysis from Gabor Co-occurrences......Page 707
Datasets......Page 708
Comparison Methods......Page 709
Results......Page 710
References......Page 711
Introduction......Page 713
Parallel Architectures......Page 714
A Proximal Point Algorithm......Page 715
Experimental Results......Page 716
Conclusion......Page 720
References......Page 721
Introduction......Page 722
Incremental PCA-HOG Descriptor......Page 723
Incremental PCA-HOG Descriptor......Page 724
Incorporate IPCA-HOG Descriptor with Particle Filter......Page 726
Experimental Results......Page 727
References......Page 729
Introduction......Page 731
Attention-Mediated Perceptual Organization......Page 732
Probabilistic Learning of Object Categories......Page 733
Learning Multi-class Classifiers of Object Categories......Page 734
Inter-categorical Typicality Analysis......Page 735
Experimental Framework......Page 736
Experimental Results......Page 737
Conclusions......Page 739
References......Page 740
Introduction......Page 741
Related Work......Page 742
Background on Particle Filter......Page 743
Defining the State Space of an Activity Using Petri Net......Page 744
Propagating Uncertainty......Page 745
Experiments......Page 747
Synthetic Bank Dataset......Page 748
ETISEO Building Entrance Dataset......Page 749
References......Page 750
Introduction......Page 751
Algorithm......Page 752
Performance Evaluation......Page 756
References......Page 759
Introduction......Page 761
Background Edge Construction......Page 763
Codebook for Edge Orientation......Page 764
Pose Recognition......Page 765
Experimental Results......Page 766
Conclusions......Page 769
References......Page 770
Introduction......Page 771
Clinical Tumor Sets......Page 772
Modeling Clinical Tumor Shapes......Page 775
References......Page 780
Introduction......Page 782
Related Work......Page 784
Parameter Control......Page 785
Discussion......Page 787
Results......Page 788
References......Page 791
Author Index......Page 792