/Subspace-Learning-for-Person-Re-identification

We propose a global and local feature transformation method for PRID. The global feature transformation matrix projects the data from different cameras to a common space. We further hypothesize that a latent basis matrix can be learnt in this space which represents the shared structure between different cameras using matrix factorization.

Primary LanguageMATLAB

Stargazers