Yet another new biometric recognition based on hand tremors acquired from leapmotion device
Main Author: | Ataş, Musa |
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Format: | Dataset |
Terbitan: |
Mendeley
, 2017
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Subjects: | |
Online Access: |
https:/data.mendeley.com/datasets/8j9gs37r4c |
ctrlnum |
0.17632-8j9gs37r4c.2 |
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fullrecord |
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<dc><creator>Ataş, 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 |
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1686587403675893760 |
score |
17.538404 |