Research Article

Facial Pain Expression Recognition in Real-Time Videos

Table 3

Performance analysis of 24 videos (UNBC database).

Sl. no.Video name (.avi)Video size (MB)Number of framesTraining timeTesting timeHR (pain) in range (%)

1aa048t2aeaff2.091739 m 22 s39 s90.23–95.88
2ak064t1aaaff3.9439621 m 11 s1 m 52 s92.80–96.12
3bg096t2aaaff2.7623212 m 36 s53 s90–93.33
4bm049t2afaff3.6535118 m 50 s1 m 35 s94.33–98.65
5bn080t1afaff3.9738120 m 30 s1 m 46 s97.11–99.9
6ch092t2aiaff5.3937419 m 43 s1 m 26 s89.42–95.33
7dn124t1aiaff4.1142022 m 40 s1 m 36 s90.22–93.33
8dr052t2aiaff4.7646724 m 47 s1 m 47 s88.99–92.22
9fn059t2aiaff4.2536719 m 56 s1 m 24 s87.45–94.22
10gf097t1aaaff5.6651627 m 22 s1 m 59 s85.88–90.67
11hs107t1afaff3.1528515 m 19 s1 m 05 s89.99–93.44
12hs107t1afunaff3.3226314 m 01 s1 m 01 s90.23–93.76
13hs107t2aaaff4.0441121 m 37 s1 m 34 s89.09–94.54
14ib109t1aiaff2.6232117 m 10 s1 m 14 s92.22–96.06
15jh123t1aeaff3.735819 m 08 s1 m 22 s91.03–96
16jk103t2aiaff3.2430015 m 32 s1 m 09 s93.33–98.09
17jl047t1aiaff5.3646424 m 11 s1 m 43 s96.41–99.98
18kz120t2aaaff1.381347 m 14 s31 s92.02–95.33
19ll042ll042t1aiaff1.681688 m 12 s38 s97.76–100
20mg066t1aaaff4.5340521 m 58 s1 m 33 s90.77–93.90
21mg101t1aiaff5.861532 m 17 s2 m 21 s94.22–98.33
22nm106t1afaff3.9935118 m 02 s1 m 21 s97.12–100
23th108t2afaff2.6427714 m 13 s1 m 04 s92.08–96.73
24vw121t1aaaff2.041799 m 54 s41 s96.42–99.33