Sajid Ali
Beijing Normal University

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

Appraising the Recital of Joints in Human Running Gait through 3D Optical Motion Sajid Ali; Zhongke Wu; Mingquan Zhou; Muhammad Aslam Asadi; Hafeez Ahmed
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 4: April 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

Recital costing of Joints in human running is biometrics evaluation technology. It has skillful series of realizations in scientific research in the last decade. In this work, we present a human running joints (hip, knee and ankle) valuation recital based on the statistical computation techniques. We use the One-way ANOVA, least significant difference (LSD) test and Bartlett's test for equality of variances to determine which joint has more variation with others joints during human running gait. These three joints rotation angle data were computed from the Biovision Hierarchical data (BVH) motion file, because these joints provide the richest information of the human lower body joints (hip, knee and ankle). The use of BVH file to estimate the participation and performance of the joints during running gait is a novel feature of our study. The experimental results indicated that, the knee joint has the decisive influence (variation) as compared to the other two joints, hip and ankle, during running gait. DOI: http://dx.doi.org/10.11591/telkomnika.v11i4.2019
Comprehensive use of Hip Joint in Gender Identification Using 3-Dimension Data Sajid Ali; Zhou Mingquan; Wu Zhongke; Abdul Razzaq; Mohamed Hamada; Hafeez Ahmed
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 6: June 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

Way of walking is a spatio-temporal phenomenon that typifies the motion characteristics of human. In this paper, we propose a human gender identification method based on the outdoor surveillance of human gait using statistical techniques and geometrical function applied to three-dimensional (3D) joint movement data. The statistical techniques are used to define the features of the joint of the human gait, and the geometrical function applied for gender recognition. Our proposed scheme is based on extraction of the concern joint (hip joint) data that provides plentiful information for gender recognition. Here the rotation angle data of a hip joint were computed from the Biovision Hierarchical data (BVH file). The use of BVH file for human gender recognition is a novel feature of our work. The results indicated that the proposed approach is highly reliable for gender recognition. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2274