title: Gait recognition with shifted energy image and structural feature extraction.
abstract: In this paper, we present a novel and efficient gait recognition system. The proposed system uses two novel gait representations, i.e., the shifted energy image and the gait structural profile, which have increased robustness to some classes of structural variations. Furthermore, we introduce a novel method for the simulation of walking conditions and the generation of artificial subjects that are used for the application of linear discriminant analysis. In the decision stage, the two representations are fused. Thorough experimental evaluation, conducted using one traditional and two new databases, demonstrates the advantages of the proposed system in comparison with current state-of-the-art systems.
authors.affiliation: King’s College London, London, UK.
authors.forename: Xiaxi
authors.initials: X
authors.lastname: Huang
authors.forename: Nikolaos V
authors.initials: NV
authors.lastname: Boulgouris
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D005684:Gait / Q000502:physiology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D051598:Whole Body Imaging / Q000379:methods*