Here we try to detect the peak of classification rate in relation to SIFT topology and number of
bins.
Figure 4.3:
Optimal Number of Bins
|
Table 4.1:
Optimal Number of Bins (see figure 4.3 on page
) and its relation to
the classification rate [%]
# of bins |
6x3 |
6x4 |
6x5 |
8x4 |
10x5 |
13x9 |
15x9 |
17x11 |
17x13 |
19x13 |
19x15 |
21x15 |
3 |
66.67 |
62.5 |
72.92 |
81.25 |
83.33 |
81.25 |
81.25 |
83.33 |
83.33 |
81.25 |
83.33 |
83.33 |
5 |
70.83 |
54.17 |
70.83 |
85.42 |
83.33 |
83.33 |
81.25 |
83.33 |
83.33 |
83.33 |
85.42 |
85.42 |
7 |
77.08 |
60.42 |
66.67 |
87.5 |
83.33 |
85.42 |
87.5 |
83.33 |
83.33 |
87.5 |
85.42 |
85.42 |
9 |
79.17 |
56.25 |
66.67 |
89.58 |
85.42 |
89.58 |
89.58 |
85.42 |
85.42 |
87.5 |
85.42 |
87.5 |
10 |
75 |
37.5 |
81.25 |
79.17 |
87.5 |
83.33 |
81.25 |
85.42 |
85.42 |
87.5 |
87.5 |
87.5 |
11 |
81.25 |
60.42 |
75 |
89.58 |
87.5 |
89.58 |
89.58 |
87.5 |
87.5 |
89.58 |
89.58 |
87.5 |
13 |
77.08 |
62.5 |
72.92 |
89.58 |
87.5 |
89.58 |
93.75 |
87.5 |
89.58 |
89.58 |
93.75 |
89.58 |
15 |
72.92 |
41.67 |
75 |
85.42 |
87.5 |
89.58 |
93.75 |
85.42 |
89.58 |
89.58 |
91.67 |
89.58 |
17 |
72.92 |
43.75 |
75 |
83.33 |
83.33 |
87.5 |
91.67 |
87.5 |
85.42 |
89.58 |
91.67 |
91.67 |
21 |
66.67 |
47.92 |
72.92 |
79.17 |
81.25 |
87.5 |
87.5 |
87.5 |
83.33 |
87.5 |
91.67 |
89.58 |
25 |
68.75 |
39.58 |
70.83 |
81.25 |
83.33 |
81.25 |
81.25 |
81.25 |
83.33 |
79.17 |
83.33 |
85.42 |
|
We can see that the best classification rate was achieved when the number of bins was between
11-15. The worst case was usually when number of bins was 10 (figure 4.3 on page
).
Another interesting thing is the overall weakness of classificator with number of bins 10. The
surrounding bins 9 and 11 have usually better power.
Another interesting thing is that SIFTs with topology 6x3 and 6x5 are both stronger classificators
than the one with topology 6x4 eventhough the classification is better with more detailed
classificators (so 6x3 should be worse than 6x4)
Table 4.2:
SIFT Topology and how this influences the classification rate(see figure 4.4 on page
)
SIFT Topology |
Classification Rate [%] |
6x3 |
81.25 |
6x4 |
62.50 |
6x5 |
81.25 |
8x4 |
89.58 |
10x6 |
75.00 |
10x5 |
87.50 |
13x9 |
89.58 |
15x9 |
93.75 |
17x11 |
87.50 |
17x13 |
89.58 |
19x13 |
89.58 |
19x15 |
93.75 |
21x15 |
91.67 |
|
Figure 4.4:
SIFT Topology and how this influences the classification rate
|
We found that the classification rate is getting better as the detail of SIFT topology is increasing
up to some level. Then the classification rate is decreasing (figure 4.4 on page
).
Kocurek
2007-12-17