Paper
10 May 2012 Context based gait recognition
Shermin Bazazian, Marina Gavrilova
Author Affiliations +
Abstract
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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shermin Bazazian and Marina Gavrilova "Context based gait recognition", Proc. SPIE 8407, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012, 84070J (10 May 2012); https://doi.org/10.1117/12.921449
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CITATIONS
Cited by 10 scholarly publications.
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KEYWORDS
Gait analysis

Databases

Biometrics

Data modeling

Information fusion

Video

Detection and tracking algorithms

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