Human Gait Feature Extraction based-on Silhouette and Center of Mass

Abstract

When someone walks, there is a repetitive movement or coordinated cycle that forms a gait. Gait is different, unique and difficult to imitate. This characteristic makes gait one of the biometrics to find out one's identity. Gait analysis is needed in the development of biometric technology, such as in the field of security surveillance and the health sector to monitor gait abnormalities. The center of mass is the unique point of every object that has a role in the study of humans walking. Each person has a different center of mass. In this research, through a series of processes in image processing such as video acquisition, segmentation, silhouette formation, and feature extraction, the center of mass of the human body can be identified using a webcam with the resolution of 640 x 480 pixels and the frame rate of 30 frames/second. The results obtained from this research were gait frames of 510 frames from 17 pedestrian videos. Segmentation process using background subtraction separates the pedestrian object image from the background. Silhouette gait was produced from a series of image enhancement processes to eliminate noise that interferes the image quality. Based on the silhouette, feature extraction provides the center of mass to distinguish each individual's gait. The sequence of center of mass can be further processed for characterizing human gait cycle for various purposes.

Authors and Affiliations

Miftahul Jannah, Sarifuddin Madenda, Tubagus Maulana Kusuma, Hustinawaty Hustinawaty

Keywords

Related Articles

A new approach of designing Multi-Agent Systems

Agent technology is a software paradigm that permits to implement large and complex distributed applications [1]. In order to assist analyzing, conception and development or implementation phases of multi-agent systems,...

Instruction Design Model for Self-Paced ICT System E-Learning in an Organization

Adopting an Information Communication and Technology (ICT) system in an organization is somewhat challenging. User diversity, heavy workload, and different skill gap make the ICT adoption process slower. This research st...

Efficiency and Performance Analysis of a Sparse and Powerful Second Order SVM Based on LP and QP

Productivity analysis is done on the new algorithm “Second Order Support Vector Machine (SOSVM)”, which could be thought as an offshoot of the popular SVM and based on its conventional QP version as well as the LP one. O...

Cloud Server Security using Bio-Cryptography

Data security is becoming more important in cloud computing. Biometrics is a computerized method of identifying a person based on a physiological characteristic. Among the features measured are our face, fingerprints, ha...

An Adaptive Approach to Mitigate Ddos Attacks in Cloud

Distributed denial of service (DDOS) attack constitutes one of the prominent cyber threats and among the hardest security problems in modern cyber world. This research work focuses on reviewing DDOS detection techniques...

Download PDF file
  • EP ID EP646204
  • DOI 10.14569/IJACSA.2019.0100961
  • Views 83
  • Downloads 0

How To Cite

Miftahul Jannah, Sarifuddin Madenda, Tubagus Maulana Kusuma, Hustinawaty Hustinawaty (2019). Human Gait Feature Extraction based-on Silhouette and Center of Mass. International Journal of Advanced Computer Science & Applications, 10(9), 462-468. https://europub.co.uk/articles/-A-646204