Comparison Analysis of Gait Classification For Human Motion Identification Using Embedded Computer

Agung Nugroho Jati (Telkom University)
Astri Novianty (Telkom University)
Nanda Septiana (Telkom University)
Leni Widia Nasution (Telkom University)

International Journal of Electrical and Computer Engineering
Vol 8, No 6: December 2018

In this paper, it will be discussed about comparison between two kinds of classification methods in order to improve security system based of human gait. Gait is one of biometric methods which can be used to identify person. K-Nearest Neighbour has parallelly implemented with Support Vector Machine for classifying human gait in same basic system. Generally, system has been built using Histogram and Principal Component Analysis for gait detection and its feature extraction. Then, the result of the simulation showed that K-Nearest Neighbour is slower in processing and less accurate than Support Vector Machine in gait classification.