Yet another new biometric recognition based on hand tremors acquired from leapmotion device
| Main Author: | Ataş, Musa |
|---|---|
| Format: | Dataset |
| Terbitan: |
Mendeley
, 2017
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| Subjects: | |
| Online Access: |
https:/data.mendeley.com/datasets/8j9gs37r4c |
Daftar Isi:
- 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.