Open AccessMultiview Running and Walking Gait Analysis using the First and Third Person Data
Author(s) -
Nikita Malik,
Sudipta Majumdar
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2070/1/012138
Subject(s) - biometrics , gait , motion (physics) , biometric data , computer science , artificial intelligence , gait analysis , movement (music) , computer vision , physical medicine and rehabilitation , motion capture , medicine , philosophy , aesthetics
Gait recognition, which allows to recognise someone from a distance, has a lot of applications. The gait of a person is commonly used as a biometric approach to identify or categorise them by gender and age. Biometric systems are a fast-growing subject that necessitates the development of creative solutions to problems that have plagued previous attempts. By initially looking at the design of a gait detection system, two different types of gait datasets have been reported and presented in this paper. While running at the same time, the first person (FP) data containing the camera motion gathered from the movement of the volunteer’s body and the third person (TP) data captured from a distant view were recorded. The dataset contains a total of 23 participants (14 males and 9 females). The discussion is expanded to include a comparison of the results obtained using TP and FP data, as well as an examination of the physiological motions recorded while running and walking.