CCA for Feature Fusion

Question

In some of the multi-modal recognition methods, they are using Canonical Correlation Analysis (CCA) to fuse the two input feature vectors into a single and also a low dimension one. Matlab has already the code for CCA which is: [A,B,r,U,V] = canoncorr(X,Y); See: http://www.mathworks.com/help/stats/canoncorr.html

I wonder how I can reach the final (fused) feature vector using this function. Can someone explain the steps or suggest a reference, please?

Answer 1

I found out how to perform the feature fusion using CCA. I wrote a Matlab code to do it and shared the code in MATLAB Central.

Detailed descriptions can be found in this paper:

M. Haghighat, M. Abdel-Mottaleb, W. Alhalabi, "Fully Automatic Face Normalization and Single Sample Face Recognition in Unconstrained Environments," Expert Systems With Applications, vol. 47, pp. 23-34, April 2016.