In person re-identification

aiming at salient color named based color descriptor（ SCNCD） features based on salient color names are robust to illumination changes

propose to fuse the SCNCD features and the LOMO features which are robust to viewpoint changes. In order to get structure information of images

the images are divided into overlapping patches and the patch features are extracted. In order to solve the problems that neural network is easy to fall into local minimum and its convergence speed is slow

momentum term is introduced. The proposed method has been tested in the most challenging public VIPeR database and PRID450 s database

and experimental results prove that recognition abilities of the fused features are obviously higher than that of the original features

and convergence speed of the improved neural network is increased obviously.