Distinguishing twins by Gait via Jackknife-Like validation in classification analysis


Mohd-Isa, Wan-Noorshahida and Abdullah, Junaidi and Eswaran, Chikkanan (2014) Distinguishing twins by Gait via Jackknife-Like validation in classification analysis. In: Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013). Lecture Notes in Electrical Engineering (285). Springer Singapore, pp. 301-308. ISBN 978-981-4585-17-0

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This paper is about analysing the uniqueness of twins by gait biometric. The motivation arises due to twins, having facial similarity may lay difficulties to a video-based recognition system employing face biometric. Gait, a biometric based on the way a person walk, can perhaps be a useful descriptor. Due to the small size data set, classification via leave-one-out cross validation may not be sufficient to test gait’s viability as a descriptor for twins. Thus, this paper proposes a jackknife-like validation in a matched-pair classification. Comparing between the results of both validation approaches, results of the proposed method have shown to be promising. The results perhaps may point to the uniqueness of each individual twin by gait biometric.

Item Type: Book Section
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 03 Mar 2014 08:48
Last Modified: 03 Mar 2014 08:48
URII: http://shdl.mmu.edu.my/id/eprint/5350


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