Summary Errors
Per Model Errors
Unexpected Crashes

Algorithms: 6

Summary Tables

Total

Algorithm
--------
Value

Blended	Mobius Voting	Best Conformal	GMDS	HKM 1 corr	HKM 2 corrs
Average Error	0.127693	0.164354	0.190213	0.503847	0.376407	0.383356
Maximal Error	0.325139	0.565471	0.561247	1.02471	1.07637	1.05846

NRW_cat

Algorithm
--------
Value

Blended	Mobius Voting	Best Conformal	GMDS	HKM 1 corr	HKM 2 corrs
Average Error	0.161419	0.210905	0.234495	0.518131	0.390226	0.378914
Maximal Error	0.386763	0.661901	0.608937	1.05145	1.06842	1.05787

NRW_horse

Algorithm
--------
Value

Blended	Mobius Voting	Best Conformal	GMDS	HKM 1 corr	HKM 2 corrs
Average Error	0.111079	0.135077	0.16064	0.5185	0.364668	0.371227
Maximal Error	0.240928	0.552939	0.53451	1.07399	1.1976	1.18873

NRW_dog

Algorithm
--------
Value

Blended	Mobius Voting	Best Conformal	GMDS	HKM 1 corr	HKM 2 corrs
Average Error	0.135329	0.152048	0.20861	0.535072	0.301738	0.302234
Maximal Error	0.343369	0.529557	0.616198	1.05517	1.06322	1.01296

NRW_wolf

Algorithm
--------
Value

Blended	Mobius Voting	Best Conformal	GMDS	HKM 1 corr	HKM 2 corrs
Average Error	0.0628037	0.0888262	0.143872	0.460783	0.313758	0.335049
Maximal Error	0.18566	0.44687	0.451267	0.932894	0.943816	0.94301

Fourleg

Algorithm
--------
Value

Blended	Mobius Voting	Best Conformal	GMDS	HKM 1 corr	HKM 2 corrs
Average Error	0.127552	0.169005	0.180892	0.450688	0.416995	0.432688
Maximal Error	0.348307	0.573285	0.554248	0.953268	1.06374	1.04269

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
cat0_to_384	Ave=0.0542528 Max=0.115191 Dense	Ave=0.0576179 Max=0.111417 Dense Sparse	Ave=0.0919025 Max=0.373372 Dense	Ave=0.051744 Max=0.126603 Dense Sparse	Ave=0.390108 Max=1.14061 Dense Sparse	Ave=0.358144 Max=1.0196 Dense Sparse
cat1_to_horse15	Ave=0.114617 Max=0.265694 Dense	Ave=0.244583 Max=0.783394 Dense Sparse	Ave=0.144712 Max=0.397348 Dense	Ave=0.345458 Max=0.785398 Dense Sparse	Ave=0.359747 Max=1.39108 Dense Sparse	Ave=0.31242 Max=1.50962 Dense Sparse
cat2_to_wolf0	Ave=0.0716051 Max=0.164664 Dense	Ave=0.106074 Max=0.302429 Dense Sparse	Ave=0.331691 Max=0.718869 Dense	Ave=0.725791 Max=1.16241 Dense Sparse	Ave=0.250474 Max=0.86724 Dense Sparse	Ave=0.2576 Max=1.20545 Dense Sparse
cat3_to_396	Ave=0.093836 Max=0.232404 Dense	Ave=0.136619 Max=0.755209 Dense Sparse	Ave=0.149266 Max=0.461526 Dense	Ave=0.7483 Max=1.25397 Dense Sparse	Ave=0.706017 Max=1.09815 Dense Sparse	Ave=0.702957 Max=1.10662 Dense Sparse
cat4_to_394	Ave=0.0933693 Max=0.224573 Dense	Ave=0.28166 Max=0.897972 Dense Sparse	Ave=0.164694 Max=0.538887 Dense	Ave=0.293632 Max=0.875203 Dense Sparse	Ave=0.287977 Max=1.15839 Dense Sparse	Ave=0.292817 Max=1.15839 Dense Sparse
cat5_to_dog8	Ave=0.0878782 Max=0.190642 Dense	Ave=0.0805755 Max=0.153227 Dense Sparse	Ave=0.135449 Max=0.424474 Dense	Ave=0.534407 Max=1.1375 Dense Sparse	Ave=0.311535 Max=0.969173 Dense Sparse	Ave=0.295318 Max=0.969173 Dense Sparse
cat6_to_387	Ave=0.181897 Max=0.635061 Dense	Ave=0.141318 Max=0.274024 Dense Sparse	Ave=0.216334 Max=0.620228 Dense	Ave=0.3152 Max=1.24858 Dense Sparse	Ave=0.425042 Max=1.37672 Dense Sparse	Ave=0.406911 Max=1.37672 Dense Sparse
cat7_to_dog5	Ave=0.142807 Max=0.643259 Dense	Ave=0.139982 Max=0.724748 Dense Sparse	Ave=0.162633 Max=0.609723 Dense	Ave=0.760937 Max=1.33372 Dense Sparse	Ave=0.312469 Max=1.34421 Dense Sparse	Ave=0.32 Max=1.34421 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
cat9_to_382	Ave=0.148421 Max=0.360171 Dense	Ave=0.225033 Max=0.867942 Dense Sparse	Ave=0.276334 Max=0.840809 Dense	Ave=0.432334 Max=0.953667 Dense Sparse	Ave=0.360383 Max=0.998807 Dense Sparse	Ave=0.350684 Max=1.02312 Dense Sparse
cat10_to_horse6	Ave=0.0951362 Max=0.211467 Dense	Ave=0.11357 Max=0.235973 Dense Sparse	Ave=0.140955 Max=0.51597 Dense	Ave=0.637315 Max=1.45462 Dense Sparse	Ave=0.324795 Max=1.08095 Dense Sparse	Ave=0.345412 Max=1.14392 Dense Sparse
horse0_to_393	Ave=0.0910199 Max=0.172253 Dense	Ave=0.0911247 Max=0.173376 Dense Sparse	Ave=0.135464 Max=0.623621 Dense	Ave=0.237528 Max=1.16566 Dense Sparse	Ave=0.373475 Max=1.31711 Dense Sparse	Ave=0.35913 Max=1.31711 Dense Sparse
horse5_to_wolf2	Ave=0.0643298 Max=0.225175 Dense	Ave=0.115401 Max=0.849706 Dense Sparse	Ave=0.114931 Max=0.375125 Dense	Ave=0.721964 Max=1.27239 Dense Sparse	Ave=0.621917 Max=1.08966 Dense Sparse	Ave=0.691189 Max=1.10748 Dense Sparse
horse6_to_dog6	Ave=0.046633 Max=0.1854 Dense	Ave=0.0535533 Max=0.21929 Dense Sparse	Ave=0.120124 Max=0.519368 Dense	Ave=0.849156 Max=1.39371 Dense Sparse	Ave=0.217821 Max=1.18306 Dense Sparse	Ave=0.214766 Max=1.18306 Dense Sparse
horse7_to_398 (Excluded)	Ave=0.0800216 Max=0.29411 Dense	Ave=0.0537081 Max=0.15301 Dense Sparse	Ave=0.133717 Max=0.467293 Dense	Ave=0.694107 Max=1.25382 Dense Sparse	Ave=0.242889 Max=1.0123 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
horse14_to_386	Ave=0.0735275 Max=0.287858 Dense	Ave=0.161061 Max=0.916452 Dense Sparse	Ave=0.130276 Max=0.464809 Dense	Ave=0.323588 Max=0.866281 Dense Sparse	Ave=0.534917 Max=1.10256 Dense Sparse	Ave=0.697948 Max=1.12019 Dense Sparse
horse15_to_dog6	Ave=0.0531242 Max=0.189266 Dense	Ave=0.0606826 Max=0.145891 Dense Sparse	Ave=0.0998366 Max=0.470733 Dense	Ave=0.239894 Max=0.901329 Dense Sparse	Ave=0.221158 Max=0.780693 Dense Sparse	Ave=0.284925 Max=0.872759 Dense Sparse
horse17_to_cat9	Ave=0.605631 Max=0.89015 Dense	Ave=0.18679 Max=0.862469 Dense Sparse	Ave=0.618178 Max=0.947557 Dense	Ave=0.289387 Max=0.989174 Dense Sparse	Ave=0.347372 Max=1.3408 Dense Sparse	Ave=0.247698 Max=1.00286 Dense Sparse
dog0_to_horse14	Ave=0.0619472 Max=0.128542 Dense	Ave=0.0665603 Max=0.1319 Dense Sparse	Ave=0.10972 Max=0.497234 Dense	Ave=0.843728 Max=1.34311 Dense Sparse	Ave=0.264491 Max=1.22286 Dense Sparse	Ave=0.298728 Max=1.29749 Dense Sparse
dog1_to_horse15	Ave=0.069908 Max=0.146562 Dense	Ave=0.121267 Max=0.29761 Dense Sparse	Ave=0.149228 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
dog2_to_horse7	Ave=0.0658107 Max=0.161107 Dense	Ave=0.107232 Max=0.854815 Dense Sparse	Ave=0.129778 Max=0.542673 Dense	Ave=0.830963 Max=1.34301 Dense Sparse	Ave=0.206402 Max=0.715494 Dense Sparse	Ave=0.15586 Max=0.656101 Dense Sparse
dog3_to_392	Ave=0.0682132 Max=0.180682 Dense	Ave=0.274095 Max=0.660785 Dense Sparse	Ave=0.193985 Max=0.546839 Dense	Ave=0.156388 Max=0.572598 Dense Sparse	Ave=0.291874 Max=0.952667 Dense Sparse	Ave=0.231165 Max=0.92989 Dense Sparse
dog5_to_cat9	Ave=0.0668186 Max=0.181674 Dense	Ave=0.174916 Max=0.957217 Dense Sparse	Ave=0.691767 Max=1.04946 Dense	Ave=0.67947 Max=1.13651 Dense Sparse	Ave=0.24057 Max=1.02775 Dense Sparse	Ave=0.231244 Max=1.02775 Dense Sparse
dog6_to_cat2	Ave=0.414611 Max=0.717944 Dense	Ave=0.69499 Max=1.09307 Dense Sparse	Ave=0.235862 Max=0.734524 Dense	Ave=0.721229 Max=1.24071 Dense Sparse	Ave=0.300028 Max=0.842428 Dense Sparse	Ave=0.299321 Max=0.842428 Dense Sparse
dog7_to_385	Ave=0.245768 Max=0.835448 Dense	Ave=0.0781961 Max=0.224697 Dense Sparse	Ave=0.196723 Max=0.765457 Dense	Ave=0.7046 Max=1.38643 Dense Sparse	Ave=0.262167 Max=1.03588 Dense Sparse	Ave=0.25613 Max=1.03588 Dense Sparse
dog8_to_385	Ave=0.702209 Max=1.08333 Dense	Ave=0.185482 Max=0.772405 Dense Sparse	Ave=0.113173 Max=0.420222 Dense	Ave=0.296207 Max=0.806287 Dense Sparse	Ave=0.334679 Max=1.04066 Dense Sparse	Ave=0.294241 Max=0.824915 Dense Sparse
dog10_to_horse6	Ave=0.0604291 Max=0.175696 Dense	Ave=0.182104 Max=0.894591 Dense Sparse	Ave=0.100029 Max=0.460486 Dense	Ave=0.820786 Max=1.32752 Dense Sparse	Ave=0.304387 Max=1.36077 Dense Sparse	Ave=0.28896 Max=1.26615 Dense Sparse
wolf0_to_dog0	Ave=0.074795 Max=0.18365 Dense	Ave=0.0769575 Max=0.114263 Dense Sparse	Ave=0.118869 Max=0.440603 Dense	Ave=0.280391 Max=0.835222 Dense Sparse	Ave=0.27458 Max=1.17871 Dense Sparse	Ave=0.164416 Max=0.774782 Dense Sparse
wolf1_to_384	Ave=0.0326398 Max=0.169716 Dense	Ave=0.0434383 Max=0.228974 Dense Sparse	Ave=0.0606109 Max=0.275198 Dense	Ave=0.0400227 Max=0.225963 Dense Sparse	Ave=0.204921 Max=0.787799 Dense Sparse	Ave=0.285769 Max=0.787799 Dense Sparse
wolf2_to_394	Ave=0.0738687 Max=0.158597 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
381_to_horse10	Ave=0.061967 Max=0.162986 Dense	Ave=0.0836972 Max=0.197978 Dense Sparse	Ave=0.10967 Max=0.443203 Dense	Ave=0.767028 Max=1.2453 Dense Sparse	Ave=0.703807 Max=1.52679 Dense Sparse	Ave=0.705038 Max=1.52679 Dense Sparse
382_to_dog10	Ave=0.0752927 Max=0.263087 Dense	Ave=0.153642 Max=0.877854 Dense Sparse	Ave=0.127804 Max=0.445045 Dense	Ave=0.2868 Max=0.859448 Dense Sparse	Ave=0.1674 Max=0.641931 Dense Sparse	Ave=0.133269 Max=0.332686 Dense Sparse
383_to_cat0	Ave=0.0553761 Max=0.147798 Dense	Ave=0.0921101 Max=0.268415 Dense Sparse	Ave=0.107438 Max=0.396382 Dense	Ave=0.332886 Max=0.687516 Dense Sparse	Ave=0.441697 Max=0.798346 Dense Sparse	Ave=0.451694 Max=0.870995 Dense Sparse
384_to_dog5	Ave=0.0704358 Max=0.268325 Dense	Ave=0.0776522 Max=0.16513 Dense Sparse	Ave=0.308995 Max=0.853909 Dense	Ave=0.817937 Max=1.36898 Dense Sparse	Ave=0.621778 Max=1.33532 Dense Sparse	Ave=0.713945 Max=1.33532 Dense Sparse
385_to_383	Ave=0.0540444 Max=0.181392 Dense	Ave=0.0691625 Max=0.193438 Dense Sparse	Ave=0.106496 Max=0.270137 Dense	Ave=0.675385 Max=1.2631 Dense Sparse	Ave=0.187799 Max=0.916051 Dense Sparse	Ave=0.213041 Max=0.916051 Dense Sparse
386_to_387	Ave=0.126689 Max=0.367716 Dense	Ave=0.0977953 Max=0.21438 Dense Sparse	Ave=0.153664 Max=0.466061 Dense	Ave=0.728794 Max=1.34138 Dense Sparse	Ave=0.747352 Max=1.39796 Dense Sparse	Ave=0.750175 Max=1.39796 Dense Sparse
387_to_cat10	Ave=0.127379 Max=0.969455 Dense	Ave=0.240864 Max=0.911109 Dense Sparse	Ave=0.132936 Max=0.40778 Dense	Ave=0.754792 Max=1.39281 Dense Sparse	Ave=0.560928 Max=1.02993 Dense Sparse	Ave=0.71561 Max=1.11974 Dense Sparse
388_to_cat4	Ave=0.098742 Max=0.232316 Dense	Ave=0.1046 Max=0.278461 Dense Sparse	Ave=0.126747 Max=0.405228 Dense	Ave=0.117264 Max=0.554859 Dense Sparse	Ave=0.173243 Max=0.600977 Dense Sparse	Ave=0.201521 Max=0.600977 Dense Sparse
389_to_381	Ave=0.0487557 Max=0.128564 Dense	Ave=0.136374 Max=0.70977 Dense Sparse	Ave=0.0683388 Max=0.243575 Dense	Ave=0.777945 Max=1.23731 Dense Sparse	Ave=0.461001 Max=0.882486 Dense Sparse	Ave=0.619546 Max=1.0552 Dense Sparse
390_to_cat3	Ave=0.0776548 Max=0.27004 Dense	Ave=0.383487 Max=1.16365 Dense Sparse	Ave=0.464919 Max=0.932374 Dense	Ave=0.777312 Max=1.42855 Dense Sparse	Ave=0.546681 Max=1.21679 Dense Sparse	Ave=0.368995 Max=1.16552 Dense Sparse
391_to_cat9	Ave=0.0678179 Max=0.214645 Dense	Ave=0.197964 Max=0.768548 Dense Sparse	Ave=0.209863 Max=0.631816 Dense	Ave=0.69274 Max=1.0754 Dense Sparse	Ave=0.608547 Max=0.926985 Dense Sparse	Ave=0.609334 Max=0.926985 Dense Sparse
392_to_386	Ave=0.105223 Max=0.39172 Dense	Ave=0.386294 Max=0.774436 Dense Sparse	Ave=0.17625 Max=0.526799 Dense	Ave=0.377964 Max=0.876002 Dense Sparse	Ave=0.629779 Max=1.00208 Dense Sparse	Ave=0.640767 Max=1.06726 Dense Sparse
393_to_dog5	Ave=0.122797 Max=0.681331 Dense	Ave=0.170868 Max=0.888653 Dense Sparse	Ave=0.742952 Max=1.42266 Dense	Ave=0.0881617 Max=0.224171 Dense Sparse	Ave=0.539139 Max=1.27769 Dense Sparse	Ave=0.748979 Max=1.27769 Dense Sparse
394_to_cat2	Ave=0.0890712 Max=0.272668 Dense	Ave=0.374584 Max=1.03963 Dense Sparse	Ave=0.238935 Max=0.746561 Dense	Ave=0.373158 Max=0.78208 Dense Sparse	Ave=0.317715 Max=1.21544 Dense Sparse	Ave=0.265005 Max=0.79512 Dense Sparse
395_to_390 (Excluded)	Ave=0.166026 Max=0.432997 Dense	Ave=0.28873 Max=1.40363 Dense Sparse	Ave=0.239382 Max=0.846064 Dense	Ave=0.819941 Max=1.43935 Dense Sparse	Ave=0.784836 Max=1.65235 Dense Sparse	XXX
396_to_dog1	Ave=0.0627233 Max=0.1598 Dense	Ave=0.0655469 Max=0.135262 Dense Sparse	Ave=0.107851 Max=0.450327 Dense	Ave=0.322891 Max=0.859776 Dense Sparse	Ave=0.279593 Max=0.996734 Dense Sparse	Ave=0.231247 Max=0.996734 Dense Sparse
397_to_394	Ave=0.0766917 Max=0.213461 Dense	Ave=0.107276 Max=0.237493 Dense Sparse	Ave=0.147878 Max=0.505262 Dense	Ave=0.767029 Max=1.34064 Dense Sparse	Ave=0.26664 Max=1.09005 Dense Sparse	Ave=0.258243 Max=1.09005 Dense Sparse
398_to_cat9 (Excluded)	Ave=0.0637235 Max=0.158675 Dense	Ave=0.149751 Max=0.632989 Dense Sparse	Ave=0.11554 Max=0.353998 Dense	Ave=0.609695 Max=1.04461 Dense Sparse	Ave=0.328194 Max=1.18766 Dense Sparse	XXX
399_to_cat2	Ave=0.623823 Max=1.03393 Dense	Ave=0.32707 Max=0.700833 Dense Sparse	Ave=0.164973 Max=0.621286 Dense	Ave=0.638754 Max=1.28159 Dense Sparse	Ave=0.623057 Max=1.0522 Dense Sparse	Ave=0.592915 Max=1.04628 Dense Sparse
400_to_wolf0	Ave=0.0595837 Max=0.212155 Dense	Ave=0.0598582 Max=0.227498 Dense Sparse	Ave=0.101299 Max=0.349918 Dense	Ave=0.301432 Max=0.833101 Dense Sparse	Ave=0.252808 Max=0.803935 Dense Sparse	Ave=0.294534 Max=0.846999 Dense Sparse

Excluded Due to Crashes

395_to_390 (1)

398_to_cat9 (1)

horse7_to_398 (1)