The Prague Texture Segmentation Datagenerator and Benchmark - Algorithms
optimized
for

The concise description of algorithms contains hyperlinks to further information (author, algorithms details, BIB entry, WWW external page).
The algorithm features are: f1 = classification (supervised segmentation), f2 = hiearchy result (manual selection), f3 = known number of regions, f4 = [reserved].
xiaofang's
celine.chinoise
f1: 0
f2: 0
f3: 1
f4: 0
sas_gmm(color+tensor), sas_gmm(color) [c=7]
weighted_color_patch, gmm_sift [c=7]
sas, gmm_lrr, sas_gmm_withoutSparseCoding
SR_multifeat [all]

List of uploaded results for 'celine.chinoise' algorithm
   benchmark label version CS OS US ME NE O C CA CO CC I II EA MS RM CI GCE LCE BCE GBCE BGM SC SSC VD L AVI NVI NMI M ARI JC DC FMI WI WII NBDE
#Colour [normal] sas_gmm(color+tensor) 56.18 8.22 9.92 26.38 27.56 13.49 17.74 72.16 80.33 83.18 19.67 3.76 79.99 70.49 5.28 80.84 16.40 10.62 28.98 23.20 80.33 73.93 73.97 14.02 77.98 5.65 18.68 79.23 9.18 72.82 66.42 78.69 79.03 78.92 79.83 7.06
Colour [normal] sas_gmm(color) c=7 66.88 13.63 11.93 8.46 8.44 4.92 6.97 79.87 85.76 88.16 14.24 2.36 85.72 78.65 4.45 86.33 11.00 5.90 21.14 16.05 85.76 81.49 81.61 9.50 85.88 3.88 13.10 85.65 6.52 80.86 75.31 85.05 85.32 85.89 85.29 5.58
Colour [normal] weighted_color_patch 30.92 4.12 26.67 37.40 35.72 41.32 28.70 53.55 67.49 63.39 32.51 6.60 62.69 51.23 9.34 64.00 20.29 14.82 43.88 38.42 67.49 61.93 58.22 22.27 60.97 8.50 28.31 65.70 16.83 54.93 50.40 65.57 66.85 59.53 76.91 9.89
#Colour [normal] weighted_color_patch noise 26.88 10.33 14.95 45.18 43.88 40.32 34.05 52.69 65.91 65.65 34.09 5.91 62.86 49.16 8.86 64.27 24.53 17.48 45.79 38.73 65.91 59.48 56.86 23.82 61.58 9.04 30.05 65.03 16.30 53.50 47.74 63.74 64.59 60.70 70.23 11.14
#Colour [normal] gmm_sift c=7 46.33 8.84 8.62 33.26 33.33 17.62 20.36 66.06 75.82 80.03 24.18 3.84 75.50 63.73 6.01 76.65 22.87 15.90 35.02 28.06 75.82 67.95 68.26 18.56 74.78 7.36 24.65 73.12 11.12 66.03 59.11 73.03 73.33 73.99 73.27 8.32
Colour [normal] sas originial 41.42 15.04 12.48 27.64 26.92 17.80 15.13 66.53 75.75 82.19 24.25 4.17 76.10 63.63 6.72 77.48 20.47 11.25 35.25 26.03 75.75 68.47 68.43 17.13 75.42 6.47 21.84 76.07 11.22 66.22 59.42 73.37 73.72 74.33 73.83 8.02
#Colour [normal] gmm_lrr 30.96 13.15 7.38 45.70 46.28 24.49 23.96 60.47 70.37 78.62 29.63 4.37 71.37 55.56 7.26 72.88 25.48 17.53 40.61 32.65 70.37 62.53 62.57 22.21 71.79 7.96 26.41 71.61 12.73 59.92 53.44 67.75 68.24 71.17 66.32 8.77
#Colour [normal] sas_gmm_withoutSparseCoding 41.44 9.92 7.08 40.76 40.86 22.52 20.14 64.51 73.99 80.10 26.01 3.96 74.47 60.99 6.89 75.71 22.63 15.76 36.54 29.66 73.99 65.83 66.36 19.60 72.59 7.35 24.66 73.03 11.68 64.47 57.73 71.91 72.25 73.82 71.38 8.70
Colour [normal] SR_multifeat all 45.57 14.56 27.86 17.99 17.58 14.76 20.63 65.36 76.12 76.95 23.88 5.18 73.17 64.18 7.49 74.36 14.68 9.40 32.16 26.88 76.12 71.39 70.07 15.46 76.62 5.91 19.57 77.52 11.17 68.58 62.59 75.81 76.54 72.03 82.58 7.63