1. A method comprising: accessing data for a first object and data for a second object; extracting a reference feature (P ji a ) from each of the first object and the second object, wherein the reference feature (P ji a ) is represented as: 
 P ji a =S a T ( Tr ji −m a ) where Tr ji is training data comprising a discriminative subspace and Tr ji ={Tr j1 , Tr j2 ,. .. , Tr ji ,. .. |j≦G} among G face classes, where m a is a reference mean, and S a is a reference manifold and S a T is a transformation matrix of S a ; comparing, by a processor, the first and second objects based at least in part upon the reference features from each of the first and second object, wherein the comparing comprises: mapping the extracted first and second reference features on the discriminative subspace to obtain a first merged feature and a second merged feature; determining a distance between the first and second merged features; and determining whether the first object and the second object are the same object comprises determining whether the first object and the second object are the same object based at least in part upon the determined distance; and determining, using a processor, whether the first object and the second object are the same object based at least in part upon the comparison.