-
Notifications
You must be signed in to change notification settings - Fork 8
/
fundamental.cfg
130 lines (92 loc) · 3.41 KB
/
fundamental.cfg
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
// example configuration file for fundamental matrix estimation
// ========================================================================================
// common RANSAC parameters
common =
{
// ransac_conf: 0.0 - 1.0 (must be float)
// specifies the confidence parameter
ransac_conf = 0.99;
// min_sample_size: int
// number of points used to generate models
min_sample_size = 7;
// inlier_threshold: float
// threshold for inlier classification
inlier_threshold = 1.5;
// max_hypotheses: int
// maximum number of samples to be drawn before aborting
max_hypotheses = 850000;
// max_solutions_per_sample: int
// number of possible solutions using the minimal sample
max_solutions_per_sample = 3;
// prevalidate_sample: true, false
// specifies whether samples are to be prevalidated prior to model generation
prevalidate_sample = true;
// prevalidate_model: true, false
// specifies whether models are to be prevalidated prior to verification against data points
prevalidate_model = true;
// degen_check: true, false
// specifies whether degeneracy testing is to be performed
degen_check = true;
// random_sampling_method: UNIFORM, PROSAC (string)
// specifies the type of random sampling to be used to generate hypotheses
random_sampling_method = "UNIFORM";
// verif_method: STANDARD, SPRT (string)
// specifies the type of model verification to be performed
verif_method = "SPRT";
// local_opt: NO_LO, LOSAC (string)
// specifies what type of local optimization is to be performed
local_opt = "LOSAC";
};
// ========================================================================================
// PROSAC parameters
prosac =
{
// max_prosac_samples: int
// number of samples after which PROSAC behaves like RANSAC
max_prosac_samples = 100000;
// beta: float
// probability of incorrect model being support by a random data point
// can be adapted to use values from sprt
beta = 0.09;
// min_stopping_length: int
min_stopping_length = 20;
// non_rand_conf: float
// find non-minimal subset with probability of randomness smaller than (1-non_rand_conf)
non_rand_conf = 0.99;
// sorted_points_path: string
// path to file containing indices of points sorted by quality scores
sorted_points_path = "./sorting.txt";
};
// ========================================================================================
// SPRT parameters
sprt =
{
time_model = 200.0;
models_per_sample = 2.38;
delta = 0.05;
epsilon = 0.15;
};
// ========================================================================================
// Local optimization parameters
losac =
{
inner_sample_size = 15;
inner_ransac_repetitions = 5;
threshold_multiplier = 2.0;
num_steps = 4;
};
// ========================================================================================
// Problem specific parameters
problem_specific =
{
// matrix_decomposition: QR, LU
matrix_decomposition = "QR";
// h_degen_threshold: float
// inlier threshold for the h-degeneracy test (set to 0.0 if not being used)
h_degen_threshold = 6.5;
// max_upgrade_samples: int
// maximum number of 2-point samples to draw in the model upgrade loop
max_upgrade_samples = 8000;
// path to file containing the input points
input_file_path = "./orig_pts.txt";
};