Download
1 / 12
Parallel Image Matrix Compression for Face Recognition
130 likes | 287 Vues
Parallel Image Matrix Compression for Face Recognition. 洪銘曎 12/31. Introduction. The canonical face recognition algorithm Eigenface and Fisherface are both based on one dimensional vector representation.
Télécharger la présentation 
Parallel Image Matrix Compression for Face Recognition
An Image/Link below is provided (as is) to download presentation
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.
Content is provided to you AS IS for your information and personal use only.
Download presentation by click this link.
While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
During download, if you can't get a presentation, the file might be deleted by the publisher.
E N D
Presentation Transcript
Parallel Image Matrix Compression for Face Recognition 洪銘曎 12/31
Introduction • The canonical face recognition algorithm Eigenface and Fisherface are both based on one dimensional vector representation. • With the high feature dimensions, face recognition often suffers from the curse of dimension problem.
I ) what is the meaning of the eigenvalue and eigenvector of the covariancematrix in 2DPCA • 2) why 2DPCA can outperform Eigenface • 3) how to reduce the dimension after 2DPCA directly.
More Related