%0 Conference Proceedings
%T Modified kNN Algorithm for Improved Recognition Accuracy of Biometrics System Based on Gait
%+ Białystok University of Technology
%A Derlatka, Marcin
%Z Part 3: Biometrics and Biometrics Applications
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 12th International Conference on Information Systems and Industrial Management (CISIM)
%C Krakow, Poland
%Y Khalid Saeed
%Y Rituparna Chaki
%Y Agostino Cortesi
%Y Sławomir Wierzchoń
%I Springer
%3 Computer Information Systems and Industrial Management
%V LNCS-8104
%P 59-66
%8 2013-09-25
%D 2013
%R 10.1007/978-3-642-40925-7_6
%K k-nearest neighbors
%K human gait recognition
%K ground reaction forces
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X The k-nearest neighbors classifier is one of the most frequently used. It has several interesting properties, though it cannot be used in utilitarian biometric systems. This paper proposes the modification of kNN algorithm which ensures correct work even in the case of an attempt at access to the system by unauthorized people. Work of the algorithm was tested on data presenting ground reaction forces (GRF), generated during human’s walk, obtained from measurements carried out on over 140 people. Differences between particular strides were determined with the Dynamic Time Warping (DTW). The recognition precision obtained was as high as 98% of biometric samples.
%G English
%Z TC 8
%2 https://inria.hal.science/hal-01496099/document
%2 https://inria.hal.science/hal-01496099/file/978-3-642-40925-7_6_Chapter.pdf
%L hal-01496099
%U https://inria.hal.science/hal-01496099
%~ SHS
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC8
%~ IFIP-CISIM
%~ IFIP-LNCS-8104