In this note, we point out that 2D-PCA is not a special case of MPCA. 2D-PCA views the rows of images as training samples that constitute m sub-training sets instead of original images, where m is equivalent to the row of images. It then uses these sub-training sets to evaluate the covariance matrix
The equivalence of two-dimensional PCA to line-based PCA
β Scribed by Liwei Wang; Xiao Wang; Xuerong Zhang; Jufu Feng
- Publisher
- Elsevier Science
- Year
- 2005
- Tongue
- English
- Weight
- 257 KB
- Volume
- 26
- Category
- Article
- ISSN
- 0167-8655
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