Summary Errors
Per Model Errors
Unexpected Crashes

Algorithms: 7

Summary Tables

Total

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs Deform. Driven
Average Error 0.0573097 0.13831 0.116578 0.3445 0.281199 0.26532 0.234603
Maximal Error 0.188632 0.581892 0.57101 0.886754 1.19797 1.07303 0.892359

Scape_1

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs Deform. Driven
Average Error 0.0505477 0.170648 0.110893 0.330582 0.285128 0.262108 0.301264
Maximal Error 0.131774 0.642494 0.580758 0.942407 1.30108 1.08136 0.987812

NRW_cat

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs Deform. Driven
Average Error 0.0600369 0.118451 0.0984193 0.361627 0.229285 0.260076 0.160611
Maximal Error 0.179963 0.724471 0.428178 0.750692 0.867366 0.968073 0.717774

NRW_centaur

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs Deform. Driven
Average Error 0.0881187 0.0301913 0.0661144 0.0399024 0.123181 0.11211 0.176599
Maximal Error 0.911857 0.162134 0.416678 0.167548 0.864636 1.03114 0.907654

NRW_horse

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs Deform. Driven
Average Error 0.064724 0.158807 0.141267 0.190753 0.264398 0.241203 0.205201
Maximal Error 0.143598 0.556819 0.682002 0.633355 1.34514 1.25151 0.877666

NRW_dog

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs Deform. Driven
Average Error 0.0635158 0.105646 0.127571 0.543864 0.387112 0.395543 0.234578
Maximal Error 0.14596 0.482478 0.535391 1.08556 1.14211 1.12287 1.01908

NRW_wolf

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs Deform. Driven
Average Error 0.076602 0.131228 0.135833 0.695097 0.277846 0.316784 0.0862432
Maximal Error 0.161278 0.958349 0.547887 1.26828 0.93555 0.93555 0.224044

Fourleg

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs Deform. Driven
Average Error 0.0838149 0.21734 0.140944 0.386756 0.313157 0.331781 0.0999866
Maximal Error 0.166055 1.06802 0.566193 0.709032 1.12742 1.12742 0.280137

NRW_michael

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs Deform. Driven
Average Error 0.0425602 0.0726083 0.151713 0.468255 0.272119 0.131006 0.302668
Maximal Error 0.088788 0.173285 0.651772 1.47554 1.35844 0.852323 1.51583

NRW_david

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs Deform. Driven
Average Error 0.0591559 0.221351 0.119238 0.215392 0.385595 0.36393 0.483591
Maximal Error 0.131605 0.674557 0.621784 0.854551 1.44896 1.44896 1.39708

NRW_victoria

Algorithm
--------
Value
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs Deform. Driven
Average Error 0.0425602 0.0726083 0.151713 0.468255 0.272119 0.131006 0.302668
Maximal Error 0.088788 0.173285 0.651772 1.47554 1.35844 0.852323 1.51583

Per Experiment Values

Values in each cell: average geodesic error, maximal geodesic error, images
Blended Mobius Voting Best Conformal GMDS HKM 1 corr HKM 2 corrs Deform. Driven
mesh059_to_mesh052 Ave=0.0446913
Max=0.138522
Dense

Ave=0.119665
Max=0.886114
Dense
Sparse
Ave=0.128115
Max=0.614296
Dense

Ave=0.481081
Max=1.33487
Dense
Sparse
Ave=0.369679
Max=1.31814
Dense
Sparse
Ave=0.32524
Max=1.31814
Dense
Sparse
Ave=0.356745
Max=1.33482
Dense
Sparse
mesh015_to_mesh054 Ave=0.048609
Max=0.135507
Dense

Ave=0.075065
Max=0.576847
Dense
Sparse
Ave=0.0841971
Max=0.456078
Dense

Ave=0.0616341
Max=0.214882
Dense
Sparse
Ave=0.177082
Max=1.37299
Dense
Sparse
Ave=0.103392
Max=0.558217
Dense
Sparse
Ave=0.0853492
Max=0.483403
Dense
Sparse
mesh019_to_mesh035 Ave=0.033521
Max=0.119815
Dense

Ave=0.053549
Max=0.214706
Dense
Sparse
Ave=0.145052
Max=0.682166
Dense

Ave=0.115682
Max=0.360398
Dense
Sparse
Ave=0.18284
Max=1.15973
Dense
Sparse
Ave=0.0888242
Max=0.436415
Dense
Sparse
Ave=0.0823105
Max=0.244695
Dense
Sparse
mesh054_to_mesh031 Ave=0.0604929
Max=0.12815
Dense

Ave=0.066676
Max=0.224938
Dense
Sparse
Ave=0.0977108
Max=0.597927
Dense

Ave=0.791176
Max=1.7056
Dense
Sparse
Ave=0.161304
Max=1.10289
Dense
Sparse
Ave=0.146374
Max=1.10289
Dense
Sparse
Ave=0.175939
Max=0.785603
Dense
Sparse
mesh023_to_mesh071 Ave=0.0482081
Max=0.137216
Dense

Ave=0.436881
Max=1.24574
Dense
Sparse
Ave=0.0827017
Max=0.471269
Dense

Ave=0.433721
Max=1.272
Dense
Sparse
Ave=0.333801
Max=1.25591
Dense
Sparse
Ave=0.443062
Max=1.25591
Dense
Sparse
Ave=0.441322
Max=1.272
Dense
Sparse
cat5_to_cat4 Ave=0.0410288
Max=0.211654
Dense

Ave=0.112301
Max=0.698762
Dense
Sparse
Ave=0.0780366
Max=0.442848
Dense

Ave=0.0646213
Max=0.321743
Dense
Sparse
Ave=0.152212
Max=0.774895
Dense
Sparse
Ave=0.188559
Max=0.976309
Dense
Sparse
Ave=0.0847884
Max=0.401388
Dense
Sparse
centaur2_to_centaur0 Ave=0.0881187
Max=0.911857
Dense

Ave=0.0301913
Max=0.162134
Dense
Sparse
Ave=0.0661144
Max=0.416678
Dense

Ave=0.0399024
Max=0.167548
Dense
Sparse
Ave=0.123181
Max=0.864636
Dense
Sparse
Ave=0.11211
Max=1.03114
Dense
Sparse
Ave=0.176599
Max=0.907654
Dense
Sparse
horse7_to_horse15 Ave=0.0332361
Max=0.113399
Dense

Ave=0.0517029
Max=0.195148
Dense
Sparse
Ave=0.128531
Max=0.820997
Dense

Ave=0.220048
Max=0.951636
Dense
Sparse
Ave=0.168133
Max=1.38086
Dense
Sparse
Ave=0.128501
Max=1.11576
Dense
Sparse
Ave=0.177042
Max=0.920686
Dense
Sparse
dog6_to_dog1 Ave=0.0415944
Max=0.143045
Dense

Ave=0.071071
Max=0.399645
Dense
Sparse
Ave=0.114695
Max=0.552157
Dense

Ave=0.699162
Max=1.27839
Dense
Sparse
Ave=0.578387
Max=1.13122
Dense
Sparse
Ave=0.606707
Max=1.0893
Dense
Sparse
Ave=0.14247
Max=0.646989
Dense
Sparse
wolf1_to_wolf2
(Excluded)
Ave=0.0090194
Max=0.117985
Dense

Ave=0.0172345
Max=0.184186
Dense
Sparse
Ave=0.0444595
Max=0.347069
Dense

Ave=0.23022
Max=0.808214
Dense
Sparse
Ave=0.199332
Max=0.969005
Dense
Sparse
Ave=0.195465
Max=0.969005
Dense
Sparse
XXX
horse10_to_393 Ave=0.0910279
Max=0.170832
Dense

Ave=0.303451
Max=1.1777
Dense
Sparse
Ave=0.146055
Max=0.584499
Dense

Ave=0.0784146
Max=0.149784
Dense
Sparse
Ave=0.348469
Max=1.31928
Dense
Sparse
Ave=0.346778
Max=1.31928
Dense
Sparse
Ave=0.11373
Max=0.336231
Dense
Sparse
390_to_dog6
(Excluded)
Ave=0.0995078
Max=0.311063
Dense

Ave=0.306097
Max=1.1814
Dense
Sparse
Ave=0.763194
Max=1.41119
Dense

Ave=0.723161
Max=1.41283
Dense
Sparse
Ave=0.44962
Max=1.35542
Dense
Sparse
Ave=0.311042
Max=1.35542
Dense
Sparse
XXX
wolf2_to_394 Ave=0.076602
Max=0.161278
Dense

Ave=0.131228
Max=0.958349
Dense
Sparse
Ave=0.135833
Max=0.547887
Dense

Ave=0.695097
Max=1.26828
Dense
Sparse
Ave=0.277846
Max=0.93555
Dense
Sparse
Ave=0.316784
Max=0.93555
Dense
Sparse
Ave=0.0862432
Max=0.224044
Dense
Sparse
dog1_to_horse15 Ave=0.069908
Max=0.146562
Dense

Ave=0.121267
Max=0.29761
Dense
Sparse
Ave=0.149216
Max=0.640509
Dense

Ave=0.273797
Max=0.798644
Dense
Sparse
Ave=0.276593
Max=1.33528
Dense
Sparse
Ave=0.248329
Max=1.31948
Dense
Sparse
Ave=0.324831
Max=1.37608
Dense
Sparse
cat8_to_dog1 Ave=0.0790449
Max=0.148273
Dense

Ave=0.124601
Max=0.75018
Dense
Sparse
Ave=0.118802
Max=0.413508
Dense

Ave=0.658632
Max=1.17964
Dense
Sparse
Ave=0.306357
Max=0.959836
Dense
Sparse
Ave=0.331594
Max=0.959836
Dense
Sparse
Ave=0.236433
Max=1.03416
Dense
Sparse
mesh032_to_gorilla8
(Excluded)
Ave=0.0759735
Max=0.164031
Dense

Ave=0.469984
Max=1.27268
Dense
Sparse
Ave=0.169726
Max=0.704079
Dense

Ave=0.284784
Max=1.2479
Dense
Sparse
Ave=0.682394
Max=1.3895
Dense
Sparse
Ave=0.709497
Max=1.39468
Dense
Sparse
XXX
mesh036_to_david10 Ave=0.0598786
Max=0.117699
Dense

Ave=0.0671791
Max=0.247183
Dense
Sparse
Ave=0.125132
Max=0.614195
Dense

Ave=0.351134
Max=1.51924
Dense
Sparse
Ave=0.398818
Max=1.41947
Dense
Sparse
Ave=0.391885
Max=1.41947
Dense
Sparse
Ave=0.799236
Max=1.63609
Dense
Sparse
michael13_to_victoria0 Ave=0.0425602
Max=0.088788
Dense

Ave=0.0726083
Max=0.173285
Dense
Sparse
Ave=0.151713
Max=0.651772
Dense

Ave=0.468255
Max=1.47554
Dense
Sparse
Ave=0.272119
Max=1.35844
Dense
Sparse
Ave=0.131006
Max=0.852323
Dense
Sparse
Ave=0.302668
Max=1.51583
Dense
Sparse
michael5_to_9
(Excluded)
Ave=0.0570346
Max=0.152548
Dense

Ave=0.600276
Max=1.49913
Dense
Sparse
Ave=0.495051
Max=1.66555
Dense

Ave=0.133005
Max=0.265212
Dense
Sparse
Ave=0.424859
Max=1.54784
Dense
Sparse
Ave=0.334144
Max=1.55909
Dense
Sparse
XXX
mesh003_to_david6 Ave=0.0584333
Max=0.14551
Dense

Ave=0.375523
Max=1.10193
Dense
Sparse
Ave=0.113345
Max=0.629374
Dense

Ave=0.0796494
Max=0.189862
Dense
Sparse
Ave=0.372371
Max=1.47845
Dense
Sparse
Ave=0.335976
Max=1.47845
Dense
Sparse
Ave=0.167946
Max=1.15807
Dense
Sparse

Excluded Due to Crashes

390_to_dog6 (1) mesh032_to_gorilla8 (1) michael5_to_9 (1) wolf1_to_wolf2 (1)