Bio-Inspired Structure Representation Based Cross-View Discriminative Subspace Learning via Simultaneous Local and Global Alignment

Table 3

Classification results (%) of all methods on 20% corrupted CMU-PIE dataset.

Methods	C1	C2	C3	C4	C5	C6
LDA	9.23 ± 0.10	8.66 ± 0.07	8.57 ± 0.13	6.27 ± 0.11	6.82 ± 0.12	6.59 ± 0.10
PCA	25.98 ± 0.06	25.99 ± 0.15	26.58 ± 0.14	21.97 ± 0.10	22.01 ± 0.19	20.15 ± 0.17
LatLRR	38.26 ± 1.04	34.67 ± 1.18	35.00 ± 0.84	36.11 ± 1.12	34.97 ± 0.74	35.76 ± 0.78
LPP	34.25 ± 0.22	30.08 ± 0.67	29.89 ± 0.93	33.27 ± 0.25	30.95 ± 0.51	31.07 ± 0.59
SRRS	74.30 ± 0.14	63.02 ± 0.19	72.79 ± 0.15	59.21 ± 0.36	68.73 ± 0.17	54.98 ± 0.27
RCVL	70.63 ± 0.08	61.39 ± 0.16	71.44 ± 0.10	57.34 ± 0.16	65.02 ± 0.09	53.05 ± 0.07
Ours	74.58 ± 0.03	64.74 ± 0.12	73.17 ± 0.07	60.86 ± 0.08	69.06 ± 0.06	56.56 ± 0.10