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[Color] Boundary Detection Benchmark: Algorithm "Brightness / Color / Texture Gradients"
This algorithm uses a combination of local brightness, color, and
texture gradients to detect boundaries. The gradients are combined
with a logistic to model the posterior probability of a boundary.
Each gradient is computed as the chi-squared difference in the
distribution of some feature in two half discs centered at a pixel and
divided in half at the putative boundary orientation. Using the 1976
CIELAB colorspace, the brightness and color gradients are given by the
difference in luminance and chrominance distributions. The texture
gradient is given by the difference in texton distributions. Textons
are computed by clustering filterbank responses using k-means, so that
they model the joint distribution of filter responses. The filters
are standard even- and odd-symmetric quadrature pair elongated linear
filters. See our NIPS and PAMI papers in the Grouping
area of the Berkeley Vision
Group web pages for additional details.
Click on an image for additional details.
#1 (119082) F=0.79
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#2 (170057) F=0.59
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#3 (58060) F=0.64
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#4 (163085) F=0.51
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#5 (42049) F=0.86
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#6 (167062) F=0.88
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#7 (157055) F=0.76
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#8 (295087) F=0.71
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#9 (24077) F=0.68
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#10 (78004) F=0.78
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#11 (220075) F=0.61
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#12 (45096) F=0.77
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#13 (38092) F=0.74
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#14 (43074) F=0.69
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#15 (16077) F=0.59
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#16 (86000) F=0.69
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#17 (101085) F=0.79
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#18 (219090) F=0.67
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#19 (89072) F=0.57
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#20 (300091) F=0.78
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#21 (126007) F=0.74
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#22 (156065) F=0.65
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#23 (76053) F=0.65
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#24 (296007) F=0.71
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#25 (175032) F=0.61
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#26 (253027) F=0.73
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#27 (304034) F=0.44
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#28 (86016) F=0.59
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#29 (103070) F=0.65
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#30 (8023) F=0.36
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#31 (260058) F=0.68
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#32 (41033) F=0.68
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#33 (291000) F=0.68
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#34 (109053) F=0.53
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#35 (130026) F=0.48
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#36 (241004) F=0.79
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#37 (108082) F=0.35
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#38 (285079) F=0.75
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#39 (147091) F=0.76
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#40 (69040) F=0.46
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#41 (14037) F=0.66
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#42 (54082) F=0.68
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#43 (189080) F=0.75
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#44 (229036) F=0.79
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#45 (62096) F=0.82
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#46 (271035) F=0.69
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#47 (167083) F=0.74
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#48 (12084) F=0.42
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#49 (69015) F=0.79
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#50 (148089) F=0.57
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#51 (160068) F=0.59
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#52 (145086) F=0.82
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#53 (216081) F=0.81
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#54 (97033) F=0.72
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#55 (182053) F=0.73
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#56 (208001) F=0.65
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#57 (19021) F=0.70
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#58 (227092) F=0.83
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#59 (134035) F=0.75
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#60 (223061) F=0.70
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#61 (253055) F=0.63
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#62 (148026) F=0.52
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#63 (210088) F=0.54
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#64 (86068) F=0.58
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#65 (3096) F=0.75
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#66 (41069) F=0.71
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#67 (21077) F=0.74
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#68 (196073) F=0.84
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#69 (108070) F=0.40
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#70 (123074) F=0.50
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#71 (376043) F=0.68
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#72 (306005) F=0.69
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#73 (38082) F=0.60
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#74 (33039) F=0.62
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#75 (108005) F=0.56
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#76 (106024) F=0.68
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#77 (302008) F=0.68
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#78 (102061) F=0.51
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#79 (197017) F=0.80
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#80 (299086) F=0.80
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#81 (37073) F=0.83
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#82 (241048) F=0.76
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#83 (65033) F=0.71
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#84 (55073) F=0.62
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#85 (66053) F=0.71
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#86 (143090) F=0.69
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#87 (85048) F=0.75
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#88 (42012) F=0.61
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#89 (351093) F=0.73
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#90 (361010) F=0.76
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#91 (175043) F=0.75
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#92 (87046) F=0.65
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#93 (105025) F=0.64
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#94 (236037) F=0.54
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#95 (101087) F=0.78
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#96 (304074) F=0.65
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#97 (296059) F=0.84
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#98 (159008) F=0.63
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#99 (385039) F=0.75
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#100 (69020) F=0.72
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Page generated on 20-Feb-2013 11:08:23.