Individual Recognition from Gait Using Feature Value Method

被引：10

作者：

Zhang, Tianxiang ^{[1
]}

Venture, Gentiane ^{[1
]}

机构：

[1] Tokyo Univ Agr & Technol, Dept Mech Syst Engn, Tokyo, Japan

来源：

CYBERNETICS AND INFORMATION TECHNOLOGIES | 2012年 / 12卷 / 03期

关键词：

Gait; Recognition; PCA; Feature vector; Exclusion method;

D O I：

10.2478/cait-2012-0024

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We propose a novel framework to recognize individuals from gait, in order to improve HRI. We collected the motion data of the torso from 13 persons' gait, using 2 IMU sensors. We developed Feature Value Method which is a PCA based classifier and we achieved an average individual recognition rate of 94% through cross-validation.

引用

页码：86 / 95

页数：10

共 50 条

[1] Individual recognition using Gait Energy Image
Han, J
Bhanu, B
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2006, 28 (02) : 316 - 322
[2] Improving Human Gait Recognition Using Feature Selection
Tafazzoli, Faezeh
Bebis, George
Louis, Sushil
Hussain, Muhammad
ADVANCES IN VISUAL COMPUTING (ISVC 2014), PT II, 2014, 8888 : 830 - 840
[3] A Gait Recognition method using HMM
Iwamoto, K
Sonobe, K
Komatsu, N
SICE 2003 ANNUAL CONFERENCE, VOLS 1-3, 2003, : 1936 - 1941
[4] On Reducing the Effect of Silhouette Quality on Individual Gait Recognition: a Feature Fusion Approach
Jia, Ning
Sanchez, Victor
Li, Chang-Tsun
Mansour, Hassan
BIOSIG 2015 PROCEEDINGS OF THE 14TH INTERNATIONAL CONFERENCE OF THE BIOMETRICS SPECIAL INTEREST GROUP, 2015,
[5] Omni-Domain Feature Extraction Method for Gait Recognition
Wan, Jiwei
Zhao, Huimin
Li, Rui
Chen, Rongjun
Wei, Tuanjie
MATHEMATICS, 2023, 11 (12)
[6] UNSUPERVISED FEATURE SELECTION METHOD FOR IMPROVED HUMAN GAIT RECOGNITION
Rida, Imad
Al Maadeed, Somaya
Bouridane, Ahmed
2015 23RD EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2015, : 1128 - 1132
[7] An optimal signal selection method based on feature neighborhood using for human gait mode recognition
Zhang, Miao
Sun, Ronglei
BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2024, 93
[8] Evaluation of different feature sets for gait recognition using skeletal data from Kinect
Dikovski, Bojan
Madjarov, Gjorgji
Gjorgjevikj, Dejan
2014 37TH INTERNATIONAL CONVENTION ON INFORMATION AND COMMUNICATION TECHNOLOGY, ELECTRONICS AND MICROELECTRONICS (MIPRO), 2014, : 1304 - 1308
[9] Gait Feature Extraction Using Dyadic Wavelet Transform and Structural Similarity for Gait Recognition
Omura, Hajime
Minamoto, Teruya
16TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY-NEW GENERATIONS (ITNG 2019), 2019, 800 : 373 - 377
[10] Genetic feature selection for gait recognition
Tafazzoli, Faezeh
Bebis, George
Louis, Sushil
Hussain, Muhammad
JOURNAL OF ELECTRONIC IMAGING, 2015, 24 (01)

← 1 2 3 4 5 →