Yet another new biometric recognition based on hand tremors acquired from leapmotion device

Main Author: Ataş, Musa
Format: Dataset
Terbitan: Mendeley , 2017
Subjects:
Online Access: https:/data.mendeley.com/datasets/8j9gs37r4c
ctrlnum 0.17632-8j9gs37r4c.2
fullrecord <?xml version="1.0"?> <dc><creator>Ata&#x15F;, Musa</creator><title>Yet another new biometric recognition based on hand tremors acquired from leapmotion device</title><publisher>Mendeley</publisher><description>This dataset is partly associated to the "Hand Tremor Based Biometric Recognition Using Leap Motion Device" paper (doi: 10.1109/ACCESS.2017.2764471 ). If you think this new dataset is useful for your studies please cite our paper above. Objective is to investigate whether hand jitter can be treated as a new behavioral biometric recognition trait in the filed od security so that imitating and/or reproducing artificially can be avoided.Dataset contains five subjects. 1024 samples each subject's spatiotemporal hand tremor signals as a time series data were acquired via leap motion device. Features are X, Y, Z and Mixed (Average) channels. Channel represents displacement value of adjacent frames (difference between current and previous positions) and finally the last item is class label having value from 1 to 5.lease read the "Hand Tremor Based Biometric Recognition Using Leap Motion Device" paper for more details and feature extraction methods. If you have any questions related to the preprocessing and/or processing the dataset please do not hesitate to contact with me via e-mail: hakmesyo@gmail.com . It should be noted that, data acquisition software was implemented in Java (Netbeans) and I utilized Processing, Open Cezeri Library and Weka tools alongside.</description><subject>Security</subject><subject>Biometrics</subject><subject>Tremor</subject><subject>Classification System</subject><type>Other:Dataset</type><identifier>10.17632/8j9gs37r4c.2</identifier><rights>Creative Commons Attribution 4.0 International</rights><rights>http://creativecommons.org/licenses/by/4.0</rights><relation>https:/data.mendeley.com/datasets/8j9gs37r4c</relation><date>2017-11-05T08:53:41Z</date><recordID>0.17632-8j9gs37r4c.2</recordID></dc>
format Other:Dataset
Other
author Ataş, Musa
title Yet another new biometric recognition based on hand tremors acquired from leapmotion device
publisher Mendeley
publishDate 2017
topic Security
Biometrics
Tremor
Classification System
url https:/data.mendeley.com/datasets/8j9gs37r4c
contents This dataset is partly associated to the "Hand Tremor Based Biometric Recognition Using Leap Motion Device" paper (doi: 10.1109/ACCESS.2017.2764471 ). If you think this new dataset is useful for your studies please cite our paper above. Objective is to investigate whether hand jitter can be treated as a new behavioral biometric recognition trait in the filed od security so that imitating and/or reproducing artificially can be avoided.Dataset contains five subjects. 1024 samples each subject's spatiotemporal hand tremor signals as a time series data were acquired via leap motion device. Features are X, Y, Z and Mixed (Average) channels. Channel represents displacement value of adjacent frames (difference between current and previous positions) and finally the last item is class label having value from 1 to 5.lease read the "Hand Tremor Based Biometric Recognition Using Leap Motion Device" paper for more details and feature extraction methods. If you have any questions related to the preprocessing and/or processing the dataset please do not hesitate to contact with me via e-mail: hakmesyo@gmail.com . It should be noted that, data acquisition software was implemented in Java (Netbeans) and I utilized Processing, Open Cezeri Library and Weka tools alongside.
id IOS7969.0.17632-8j9gs37r4c.2
institution Universitas Islam Indragiri
affiliation onesearch.perpusnas.go.id
institution_id 804
institution_type library:university
library
library Teknologi Pangan UNISI
library_id 2816
collection Artikel mulono
repository_id 7969
city INDRAGIRI HILIR
province RIAU
shared_to_ipusnas_str 1
repoId IOS7969
first_indexed 2020-04-08T08:14:05Z
last_indexed 2020-04-08T08:14:05Z
recordtype dc
_version_ 1686587403675893760
score 17.538404