Fusing Two Kinds of Virtual Samples for Small Sample Face Recognition

Table 3

Classification error rates of different algorithms on the Yale database.

The number of training samples	1	2	3
CRC-original	0.3733	0.1556	0.1083
CRC-mirror face	0.2800	0.1259	0.0333
CRC-symmetrical face	0.3067	0.1037	0.0500
CRC-the proposed scheme	0.2200	0.0889	0.0250
INNC	0.3733	0.2296	0.1833
INNC-mirror face	0.2800	0.1852	0.1250
INNC-symmetrical face	0.3067	0.2000	0.1583
INNC-the proposed scheme	0.2200	0.1630	0.1000
SFRFR	0.3733	0.2148	0.1417
SFRFR-mirror face only	0.2800	0.2000	0.0833
SFRFR-symmetrical face only	0.3067	0.1778	0.1167
SFRFR-the proposed scheme	0.2200	0.1333	0.0417
TPTSR	0.3733	0.1926	0.1417
TPTSR-mirror face only	0.2800	0.1259	0.0333
TPTSR-symmetrical face only	0.3067	0.1037	0.0500
TPTSR-the proposed scheme	0.2200	0.0889	0.0250