Person re-identification using mid-level features with vertical global appearance constraint - Yadong WANG; Rong ZHANG; Huihui JIANG; Lijun GUO (Dianxin kexue)
Mid-level features with the semantic information can provide stronger discrimination in the person re-identification than low-level features.But like the low-level features,the mid-level features also use local feature matching methods and easily leads mismatch problem when different pedestrians have similar appearance features in some local areas.Considering the same pedestrians are more similar than different pedestrians in the vertical direction since pedestrians are almost always in a standing position,global vertical appearance constraints was introduced.Furtherly,a method for person re-identification was proposed which fuses the low-level densely patch-matching and the mid-level features with the global vertical appearance constraints.Experimental results show that the proposed algorithm can achieve a higher hit rate than the existing methods on the most challenging public VIPeR database and CUHK01 database.