Context based gait recognition

被引：1

作者：

Bazazian, Shermin ^{[1
]}

Gavrilova, Marina ^{[1
]}

机构：

[1] Univ Calgary, Dept Comp Sci, Calgary, AB T2N 1N4, Canada

来源：

MULTISENSOR, MULTISOURCE INFORMATION FUSION: ARCHITECTURES, ALGORITHMS, AND APPLICATIONS 2012 | 2012年 / 8407卷

关键词：

Biometrics; gait recognition; information fusion; context-based model; behavioral patterns; MOTION; IMAGE;

D O I：

10.1117/12.921449

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Gait recognition has recently become a popular topic in the field of biometrics. However, the main hurdle is the insufficient recognition rate in the presence of low quality samples. The main focus of this paper is to investigate how the performance of a gait recognition system can be improved using additional information about behavioral patterns of users and the context in which samples have been taken. The obtained results show combining the context information with biometric data improves the performance of the system at a very low cost. The amount of improvement depends on the distinctiveness of the behavioral patterns and the quality of the gait samples. Using the appropriate distinctive behavioral models it is possible to achieve a 100% recognition rate.

引用

页数：6

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