1,a) 1,b) 2,c) 1,d) Gait motion descriptors 1. 12 1 Osaka University 2 Drexel University a) higashiyama@am.sanken.osaka-u.ac.jp b) makihara@am.sanken.osaka-u.ac.jp c) kon@drexel.edu d) yagi@am.sanken.osaka-u.ac.jp [1] DNA ATM [2] 2 1
Urtasun [3] Spencer [4] Han Bhanu[5] Gait energy image (GEI) Makihara [6] (Frequency domain feature, FDF) Bashir [8] 1 Gait entropy image (GEnI) Lam [9] Gait flow image (GFI) Bashir [10] GEnI GEI Masked GEI based on GEnI (MGEI) Wang [11] 4 1 Chrono-gait image (CGI) Kobayashi Otsu[12] 251 (Cubic higher-order local auto-corelation, CHLAC) Bashir [13] Gait motion descriptor (GMD) Iwama [14] 4,000 (GEI FDF GEnI GFI MGEI CGI) (1) (2) (3) (a) GEI (b) FDF (c) GENI (d) MGEI (e) GFI (f) CGI (g) CHLAC (h) GMD 1 2 2. 2.1 [7] 1 [6] GEI GEI [14] 1(a) GEI 2
FDF 1 FDF GEI 0 GEI GEI 1(b) FDF GEnI GEI GEnI GEI 0 GEI GEI 1(c) GEnI MGEI GEI GEnI GEnI GEI MGEI 1(d) GEI GEnI GFI GFI 1(e) GFI CGI 4 1 CGI 1(f) CGI 2.2 t t + n CHLAC CHLAC CHLAC 1(g) CHLAC 2.3 GMD GFI GMD GMD 1(h) GMD GMD 3. 3.1 P G D x P i R D (i =1,...,N P ) x G j RD (j =1,...,N G ) N P N G P G ( ) P i x P i G j x G j M i,j M i,j = x P i x G j (1) M M i,j 3.2 M =min i,j M i,j (2) 3
1 OU-ISIR Gait Database, The Treadmill Dataset Dataset A 9 14 20 Dataset B 32 21 47 (a) PCA (b) LDA 2 GEI (Linear discriminant analysis, LDA) (Principal component analysis, PCA) (LDA) 2(a) GEI PCA 2 S W S B S W = S B = N class i=1 N class i=1 N i features j=1 (x i,j m i )(x i,j m i ) T (3) N i features(m i m)(m i m) T (4) S W x = λs B x,x 0 (5) N class N features i i x i,j i j m i i m 2(b) GEI LDA 2 PCA ( 2(a)) LDA ( 2(b)) 4. 3 ( ) ( ) 4.1 The OU-ISIR Gait Database, The Treadmill Dataset [15] Dataset A B Dataset A 2km/h 10km/h 1km/h 34 Dataset B 32 68 1 3 DatasetA 2 Dataset B 1 31 4.2 1 1 (Vefirication) 1 N (Identification) 1 1 (False rejection rate, FRR) (False acceptance rate, FAR) (Receiver Operating Characteristics, ROC) 4
(a) ROC ( ) (c) ROC ( ) (b) CMC ( ) (d) CMC ( ) 4(a), (b) ROC CMC 4(c), (d) ROC CMC 4(e) (f) 1 GEI FDF GEnI MGEI ( 4(a), (b) ) ( 4(c), (d)) GEI FDF GEnI MGEI GEnI MGEI GEI FDF 4(e), (f) (e) (f) 1 4 1 1 (Equal error rate, EER) 1 1 1 N N N (Cumulative matching characteristics, CMC) CMC 3 90% 3 90% 1 4.3 4.4 5 1 1 6 1 N 7(a) 7(b) 1 GFI GMD GEI FDF 5. GEI GMD 5
(a) 2 km/h vs. 4 km/h (b) 2 km/h vs. 6 km/h (a) 2 km/h vs. 4 km/h (b) 2 km/h vs. 6 km/h (c)2km/hvs.8km/h (d) 2 km/h vs. 10 km/h (c)2km/hvs.8km/h (d) 2 km/h vs. 10 km/h (e)4km/hvs.6km/h (f) 4 km/h vs. 8 km/h (e)4km/hvs.6km/h (f) 4 km/h vs. 8 km/h (g) 4 km/h vs. 10 km/h (h) 6 km/h vs. 8 km/h (g) 4 km/h vs. 10 km/h (h) 6 km/h vs. 8 km/h (i) 6 km/h vs. 10 km/h (j) 8 km/h vs. 10 km/h 5 ROC (i) 6 km/h vs. 10 km/h (j) 8 km/h vs. 10 km/h 6 CMC 8(a) 8(d) GEI, GMD 8(b) 8(c) 8(e) 8(f) 8(g) 8(h) GEI GMD 2 GMD 6
(a) (b) (c) (a) (b) 1 7 1 (d) (e) (f) (a) (b) (c) (g) (h) (d) (e) (f) 9 : : : GEI GMD (g) (h) GEI GFI (g) (h) 8 : : : GEI GMD (g) (h) GEI GFI GMD GEI 9(a) 9(d) GEI GMD 9(b) 9(c) 9(e) 9(f) 9(g) 9(h) GMD 2 GEI GMD GEI GMD GEI GMD 6. 7
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