A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “car28”

This page shows the benchmarks results for the dataset instance “car28”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -75.7.

Run time 1s

method value bound optimal accuracy
dd-ls0 -75.678 -75.7886 yes 45.45%
dd-ls3 -39.8363 -100.409 no 29.55%
dd-ls4 -36.6201 -103.239 no 15.91%
fgmd inf -inf no
fm-bca -75.3961 -83.1429 no 54.55%
fm -75.2051 -146.368 no 56.82%
fw -54.3762 -inf no 2.27%
ga -71.7287 -inf no 38.64%
hbp inf -inf no
ipfps -68.2957 -inf no 65.91%
ipfpu -62.579 -inf no 54.55%
lsm -50.7508 -inf no 29.55%
mp -72.2724 -82.8016 no 70.45%
mp-fw -75.0781 -83.5099 no 52.27%
mpm -34.8182 -inf no 4.55%
mp-mcf -73.037 -82.4464 no 50.00%
pm -32.9282 -inf no 4.55%
rrwm -60.7713 -inf no 45.45%
sm -53.4134 -inf no 45.45%
smac -49.6144 -inf no 38.64%

Run time 10s

method value bound optimal accuracy
dd-ls0 -75.6956 -75.6956 yes 45.45%
dd-ls3 -52.6093 -81.8613 no 40.91%
dd-ls4 -36.6201 -97.8514 no 15.91%
fgmd inf -inf no
fm-bca -75.3961 -83.1214 no 54.55%
fm -75.4843 -146.368 no 54.55%
fw -54.3762 -inf no 2.27%
ga -71.7287 -inf no 38.64%
hbp inf -inf no
ipfps -68.2957 -inf no 65.91%
ipfpu -62.579 -inf no 54.55%
lsm -50.7508 -inf no 29.55%
mp -72.2724 -82.7878 no 70.45%
mp-fw -75.4163 -81.5616 no 47.73%
mpm -34.8182 -inf no 4.55%
mp-mcf -73.037 -79.9718 no 50.00%
pm -32.9282 -inf no 4.55%
rrwm -60.7713 -inf no 45.45%
sm -53.4134 -inf no 45.45%
smac -49.6144 -inf no 38.64%

Run time 100s

method value bound optimal accuracy
dd-ls0 -75.6956 -75.6956 yes 45.45%
dd-ls3 -75.6956 -75.6956 yes 45.45%
dd-ls4 -44.0976 -82.8535 no 38.64%
fgmd -68.7043 -inf no 29.55%
fm-bca -75.3961 -83.1214 no 54.55%
fm -75.4843 -146.368 no 54.55%
fw -54.3762 -inf no 2.27%
ga -71.7287 -inf no 38.64%
hbp -74.5363 -88.1266 no 52.27%
ipfps -68.2957 -inf no 65.91%
ipfpu -62.579 -inf no 54.55%
lsm -50.7508 -inf no 29.55%
mp -74.8335 -82.7878 no 56.82%
mp-fw -75.6956 -76.9032 yes 45.45%
mpm -34.8182 -inf no 4.55%
mp-mcf -75.161 -76.765 no 47.73%
pm -32.9282 -inf no 4.55%
rrwm -60.7713 -inf no 45.45%
sm -53.4134 -inf no 45.45%
smac -49.6144 -inf no 38.64%

Run time 300s

method value bound optimal accuracy
dd-ls0 -75.6956 -75.6956 yes 45.45%
dd-ls3 -75.6956 -75.6956 yes 45.45%
dd-ls4 -74.7299 -76.313 no 56.82%
fgmd -68.7043 -inf no 29.55%
fm-bca -75.3961 -83.1214 no 54.55%
fm -75.4843 -146.368 no 54.55%
fw -54.3762 -inf no 2.27%
ga -71.7287 -inf no 38.64%
hbp -74.5363 -88.1266 no 52.27%
ipfps -68.2957 -inf no 65.91%
ipfpu -62.579 -inf no 54.55%
lsm -50.7508 -inf no 29.55%
mp -74.8335 -82.7878 no 56.82%
mp-fw -75.6956 -76.5671 yes 45.45%
mpm -34.8182 -inf no 4.55%
mp-mcf -75.5607 -76.5416 no 52.27%
pm -32.9282 -inf no 4.55%
rrwm -60.7713 -inf no 45.45%
sm -53.4134 -inf no 45.45%
smac -49.6144 -inf no 38.64%

Other Results for this Dataset

Accumulated results for whole dataset: car

Results for individual instances of the dataset: