📄 orignal gmm versus trained.txt
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orignal GMM:
skinMOG = [...
73.53 29.94 17.76 765.40 121.44 112.80 0.0294;
249.71 233.94 217.49 39.94 154.44 396.05 0.0331;
161.68 116.25 96.95 291.03 60.48 162.85 0.0654;
186.07 136.62 114.40 274.95 64.60 198.27 0.0756;
189.26 98.37 51.18 633.18 222.40 250.69 0.0554;
247.00 152.20 90.84 65.23 691.53 609.92 0.0314;
150.10 72.66 37.76 408.63 200.77 257.57 0.0454;
206.85 171.09 156.34 530.08 155.08 572.79 0.0469;
212.78 152.82 120.04 160.57 84.52 243.90 0.0956;
234.87 175.43 138.94 163.80 121.57 279.22 0.0763;
151.19 97.74 74.59 425.40 73.56 175.11 0.1100;
120.52 77.55 59.82 330.45 70.34 151.82 0.0676;
192.20 119.62 82.32 152.76 92.14 259.15 0.0755;
214.29 136.08 87.24 204.90 140.17 270.19 0.0500;
99.57 54.33 38.06 448.13 90.18 151.29 0.0667;
238.88 203.08 176.91 178.38 156.27 404.99 0.0749];
nonskinMOG = [...
254.37 254.41 253.82 2.77 2.81 5.46 0.0637;
9.39 8.09 8.52 46.84 33.59 32.48 0.0516;
96.57 96.95 91.53 280.69 156.79 436.58 0.0864;
160.44 162.49 159.06 355.98 115.89 591.24 0.0636;
74.98 63.23 46.33 414.84 245.95 361.27 0.0747;
121.83 60.88 18.31 2502.24 1383.53 237.18 0.0365;
202.18 154.88 91.04 957.42 1766.94 1582.52 0.0349;
193.06 201.93 206.55 562.88 190.23 447.28 0.0649;
51.88 57.14 61.55 344.11 191.77 433.40 0.0656;
30.88 26.84 25.32 222.07 118.65 182.41 0.1189;
44.97 85.96 131.95 651.32 840.52 963.67 0.0362;
236.02 236.27 230.70 225.03 117.29 331.95 0.0849;
207.86 191.20 164.12 494.04 237.69 533.52 0.0368;
99.83 148.11 188.17 955.88 654.95 916.70 0.0389;
135.06 131.92 123.10 350.35 130.30 388.43 0.0943;
135.96 103.89 66.88 806.44 642.20 350.36 0.0477];
trained GMM over all 8 images with 2 iterations per image using first approach:
skinMOG =
37.4484 32.5658 34.1843 13.8999 4.3041 6.2758 0.0723
182.0000 185.0000 192.0000 0.0000 0.0000 0.0000 0
94.7552 99.6847 111.0957 17.2699 19.5284 28.4164 0.1212
142.9789 145.5472 153.2264 16.9915 11.5471 17.9825 0.0134
120.9929 80.2765 74.3183 36.5524 17.6171 5.0302 0.0253
182.0000 188.0000 186.0000 0.0000 0.0000 0.0000 0
112.4719 81.5838 75.4216 32.0925 9.9314 5.4775 0.0926
168.4660 171.4826 178.6172 8.2754 3.6815 3.2656 0.0786
163.5939 166.8673 174.5367 4.8418 1.2531 1.9210 0.0231
179.0000 181.0000 180.0000 0.0000 0.0000 0.0000 0
131.5429 91.3794 85.1058 80.9489 37.2305 30.9587 0.4317
103.1082 72.8879 69.4870 87.9763 13.7888 9.9340 0.0837
135.0000 96.0000 89.0000 0.0000 0.0000 0.0000 0
142.6915 144.9823 152.0000 18.8445 7.9394 0.0000 0.0019
76.7001 57.6445 58.2287 232.1433 9.9674 20.2618 0.0562
181.0000 185.0000 188.0000 0.0000 0.0000 0.0000 0
nonskinMOG =
254.3700 254.4100 253.8200 2.7700 2.8100 5.4600 0
26.0199 22.7637 23.9363 2.3893 2.0352 2.0911 0.0564
85.5143 89.4215 97.6160 12.3674 9.2640 17.9022 0.0905
159.2924 162.7913 170.4675 9.7654 3.8964 5.4984 0.0279
90.3027 65.5843 62.7222 60.4085 7.2927 9.6805 0.0371
50.4974 40.3170 42.1664 91.5191 7.9992 11.1414 0.0394
156.4721 158.3457 164.5596 6.0494 1.1693 3.6613 0.0088
185.2112 184.5222 189.3651 12.6228 10.2581 8.7647 0.3340
65.4967 49.3106 50.3677 158.3785 9.3339 12.3695 0.0377
31.0593 27.3243 28.7598 4.8150 2.6862 3.2846 0.1108
76.8143 80.9796 88.3997 6.6987 6.0730 6.1805 0.0352
182.0000 188.0000 186.0000 0.0000 0.0000 0.0000 0
175.6366 177.1109 183.1107 10.3601 3.4434 3.4622 0.1473
151.4817 153.8402 160.7890 9.5545 4.8666 11.1621 0.0164
123.6912 122.7599 131.2196 136.7536 112.7450 122.7393 0.0293
69.2796 70.0922 76.8519 47.5771 20.1546 23.0501 0.0294
trained GMM over image 1, 2, and 3 with 5 EM iterations using second approach:
skinMOG =
44.7533 37.7986 37.6286 54.9015 8.4493 8.2369 0.0579
192.9774 195.0191 194.0191 0.0235 0.0209 0.0209 0.0000
111.5958 116.2774 119.0166 61.1048 58.4686 63.6481 0.0433
148.0359 149.1413 148.2574 40.6585 4.5243 4.9476 0.0984
118.1438 81.8271 73.7301 13.3746 6.1385 2.6059 0.0075
190.4370 191.8304 191.7016 2.6987 3.2964 5.7048 0.0000
106.3561 76.8091 68.2218 64.6643 19.3080 15.2999 0.0016
169.8269 171.1283 171.4325 11.5098 6.4394 11.7756 0.3477
165.1209 166.8360 166.9714 5.5512 2.9833 4.0836 0.0001
180.1756 180.4754 178.1448 1.6843 1.4019 3.7059 0.0001
123.5026 86.7994 77.1792 54.5835 16.9132 12.1807 0.0979
104.2707 75.4331 66.9675 62.0316 15.9075 14.0191 0.1945
141.1892 98.0875 89.2599 8.4821 7.1792 5.7496 0.0020
155.5398 151.8719 148.7651 3.2054 4.5327 3.5264 0.0000
75.5901 56.4934 51.2757 75.3747 16.4189 9.3327 0.1364
186.9220 188.2437 186.9079 1.0000 1.2430 3.1456 0.0126
nonskinMOG =
254.3700 254.4100 253.8200 2.7700 2.8100 5.4600 0
23.5097 22.0467 22.7638 1.4102 1.4765 1.1768 0.0118
85.2345 90.2972 94.2765 30.7530 29.0714 35.0494 0.0872
160.4023 162.0840 162.6603 22.6073 15.5500 19.9247 0.3192
84.8915 66.0487 60.3606 118.0346 14.1118 28.3591 0.0966
57.1648 46.4521 43.6943 49.1834 7.5995 6.2568 0.0275
154.6064 157.0675 157.9592 24.4015 9.5154 16.0532 0.0011
183.2362 184.1715 182.2585 4.8395 4.4549 5.3515 0.0575
63.4963 52.0354 49.9144 65.0561 38.1920 48.5476 0.0236
31.4531 28.9689 29.5101 16.2701 9.7369 9.5801 0.0723
74.0639 78.5714 82.1688 9.6143 10.1038 11.9016 0.0559
189.7216 191.1085 190.4244 0.9542 0.5608 0.7421 0.0015
177.7338 178.3359 177.0879 6.4857 3.9539 7.2200 0.0808
149.9984 153.3371 154.1600 19.8715 5.4894 12.8168 0.0961
133.2217 138.8196 140.1573 35.3527 32.9575 43.3483 0.0603
85.9253 76.0398 75.0742 433.1501 28.1290 12.4671 0.0087
trained GMM over image 6, 7, and 8 with 5 EM iterations using second approach:
skinMOG =
41.6447 35.2823 35.9930 29.8428 5.9784 8.9809 0.0545
194.0000 193.0000 199.0000 0.0000 0.0000 0.0000 0.0000
142.1556 99.3637 91.8058 14.1894 17.0905 12.9976 0.0551
143.6498 147.7534 147.0840 10.7727 6.4352 17.8835 0.0341
123.2552 85.9811 76.0611 32.2166 6.7989 9.6026 0.0101
191.0167 190.0384 195.6070 0.2197 0.2739 0.4582 0.0000
119.3151 82.4800 73.1268 46.4358 14.3806 10.9444 0.0071
173.1249 173.8657 173.4414 7.0529 3.7856 18.1803 0.2838
168.7370 169.4032 167.8412 5.9719 2.1621 3.0726 0.0001
181.9184 181.2747 179.6105 1.4993 1.6664 8.7088 0.0001
130.3380 90.4254 81.4435 45.2153 18.1375 21.4221 0.2225
110.2164 77.1093 68.6713 88.4236 22.2344 22.4008 0.2286
145.8745 97.8390 94.6099 1.9823 4.0874 2.7996 0.0004
148.3840 152.1493 151.8639 13.8744 9.1780 23.6726 0.0000
80.9563 58.5946 54.0590 82.4675 23.5104 12.7832 0.0786
190.0999 189.2557 193.9862 1.4718 1.4862 4.5545 0.0250
nonskinMOG =
254.3700 254.4100 253.8200 2.7700 2.8100 5.4600 0
23.9508 21.2153 22.1509 1.7749 0.7985 0.8139 0.0176
91.6198 96.7122 102.4412 37.4938 46.4414 68.9631 0.1773
164.2268 165.4725 165.0811 24.0270 13.0974 20.3770 0.1810
87.7964 67.7558 62.6511 150.3346 17.7457 38.1562 0.1004
53.1539 42.3764 42.4689 70.7084 7.0153 10.9279 0.0180
154.4380 157.9877 158.0056 13.6884 7.9559 11.8391 0.0029
184.7817 184.0624 187.4688 5.4987 4.1501 12.4569 0.0723
64.2351 50.6718 49.7120 91.9255 22.9586 35.4645 0.0341
30.6932 27.0072 27.8285 13.1068 7.6915 8.4944 0.1127
79.0041 82.4463 85.2473 12.4593 11.3240 15.5032 0.0803
191.5000 190.5074 196.1684 0.2675 0.2816 0.4069 0.0012
179.8875 179.6710 180.5323 7.0916 3.0348 13.5246 0.1019
151.4520 155.4066 155.2628 12.7896 8.3646 13.2259 0.0383
128.1084 130.7246 132.1620 106.3594 105.6891 92.2336 0.0322
116.6416 83.0016 76.8518 223.0543 16.1261 12.2306 0.0299
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