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

Table 2

Classification results (%) of all methods on 10% corrupted CMU-PIE dataset.

Methods	C1	C2	C3	C4	C5	C6
LDA	20.45 ± 0.04	21.01 ± 0.06	19.16 ± 0.17	16.42 ± 0.12	13.64 ± 0.15	14.96 ± 0.05
PCA	48.09 ± 0.74	46.90 ± 0.25	47.74 ± 0.31	47.99 ± 0.08	46.90 ± 0.10	46.63 ± 0.06
LatLRR	59.14 ± 1.82	60.38 ± 1.10	57.94 ± 0.81	58.10 ± 1.24	57.03 ± 0.56	56.98 ± 0.96
LPP	38.47 ± 0.27	34.97 ± 0.80	37.85 ± 0.47	38.06 ± 0.24	33.16 ± 0.63	35.77 ± 0.57
SRRS	69.54 ± 0.41	66.91 ± 0.96	70.02 ± 0.96	68.89 ± 0.31	70.28 ± 0.97	65.64 ± 0.51
RCVL	87.14 ± 0.04	78.10 ± 0.07	85.52 ± 0.12	77.75 ± 0.07	86.87 ± 0.10	76.09 ± 0.05
Ours	88.68 ± 0.05	79.22 ± 0.02	87.31 ± 0.04	79.75 ± 0.11	90.69 ± 0.09	78.39 ± 0.04