Issue Number: Vol. 1, No. 2
Year of Publication: Aug - 2011
Page Numbers: 358-370
Authors: Hu Ng, Hau-Lee Ton, Wooi-Haw Tan, Timothy Tzen-Vun Yap, Pei-Fen Chong, Junaidi Abdullah
Journal Name: International Journal of New Computer Architectures and their Applications (IJNCAA)
- Hong Kong


This paper presents a human identification system based on automatically extracted gait features. The proposed approach consists of three parts: extraction of human gait features from enhanced human silhouette, smoothing process on extracted gait features and classification by three classification techniques: fuzzy k- nearest neighbour, linear discriminate analysis and linear support vector machine. The gait features extracted are height, width, crotch height, step-size of the human silhouette and joint trajectories. To improve the classification performance, two of these extracted gait features are smoothened before the classification process in order to alleviate the effect of outliers. The proposed approach has been applied on SOTON covariate database, which comprises eleven subjects walking bidirectional in a controlled indoor environment with thirteen different covariate factors that vary in terms of apparel, walking speed, shoe types and carrying objects. From the experimental results, it can be concluded that the proposed approach is effective in human identification from a distance over various covariate factors and different classification techniques.