The symmetrical decomposition is a powerful method to extract features for image recognition. It reveals the significant discriminative information from the mirror image of symmetr...
The null space-based LDA takes full advantage of the null space while the other methods remove the null space. It proves to be optimal in performance. From the theoretical analysi...
The null space of the within-class scatter matrix is found to express most discriminative information for the small sample size problem (SSSP). The null space-based LDA takes full ...
Linear Discriminant Analysis (LDA) is popular feature extraction technique for face recognition. However, it often suffers from the small sample size problem when dealing with the...
The null space N(St) of total scatter matrix St contains no useful information for pattern classification. So, discarding the null space N(St) results in dimensionality reduction ...
Wen-Sheng Chen, Pong Chi Yuen, Jian Huang, Jian-Hu...