Fusion of Gait and Facial Features using Coupled Projections for People Identification at a Distance

A novel feature-level fusion scheme for people identification at a distance has been developed by coupling gait feature with facial feature. The proposed coupled projections based method first maps the heterogeneous features from gait and face into a unified subspace to minimize the distance between the two features extracted from the same individual. The fusion features are obtained by computing the mean of the two projecting features from the same person in the coupled subspace. Experimental results demonstrate that the proposed feature-level fusion scheme outperforms the match score-level and two other feature-level fusion schemes in the application of access control at a distance.