Gait recognitin using motion capture data

Abstract

Gait recognition is an emergent technique in human identification that has been used widely in surveillance and forensic applications. The literature confirmed that accurate results can be found in gait identification using motion capture approach. By using motion capture technique, some difficulties in acquiring precise data can be avoided as the motion capture system captures the exact coordinate of each body points. This paper investigates the recognition of gait using motion capture data. Normalization method is applied to constant the data. Principle Component Analysis (PCA) is used to reduce the dimensionality of the constant gait motion data. The principle components obtained were then being matched using Euclidean Distance method between the sample and subject data. Results from the experiments show that the proposed technique is successfully recognized a person by using gait motion capture data.