Human Identification Based on Gait Motion Capture Data

被引：0

作者：

Josinski, Henryk ^{[1
,2
]}

Switonski, Adam ^{[1
,2
]}

Jedrasiak, Karol ^{[1
]}

Kostrzewa, Daniel ^{[2
]}

机构：

[1] Polish Japanese Inst Informat Technol, PL-41902 Bytom, Poland

[2] Silesian Tech Univ, PL-44101 Gliwice, Poland

来源：

INTERNATIONAL MULTICONFERENCE OF ENGINEERS AND COMPUTER SCIENTISTS, IMECS 2012, VOL I | 2012年

关键词：

Terms gait motion capture data; tensor objects; dimensionality reduction; multilinear principal component analysis (MPCA); data classification; RECOGNITION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The authors present results of the research aiming at human identification based on gait motion capture data. Second-order tensor objects were chosen as the appropriate representation of data. High-dimensional tensor samples were reduced by means of the multilinear principal component analysis (MPCA). For the purpose of classification the following methods from the WEKA library were used: k Nearest Neighbors (kNN), Naive Bayes, Multilayer Perceptron, and Radial Basis Function Network. The maximum value of the correct classification rate (CCR) equal to 95.71% was achieved for the classifier based on the multilayer perceptron.

引用

页码：507 / 510

页数：4

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