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.

A metric learning method for person re-identification