Person re-identification, identifying the same person in database from non-overlapping camera views, is a challenging task. To reduce the influence of foggy weather on person re-identification, dark channel prior is used to remove haze from input image first. Then, local maximal occurrence representation and metric learning is used to identify the same person’s images which remove haze. Experimental results show that the recognition rate of haze removed achieving 41.75% rank-1 and 81.26% rank-10, is higher than the recognition rate without haze removing which achieve 35.64 % rank-1and 46.75% rank-10.