Szczegóły publikacji
Opis bibliograficzny
Application of elastic principal component analysis to person recognition based on screen gestures / Mateusz Baran, Leszek SIWIK, Krzysztof Rzecki // W: Artificial Intelligence and Soft Computing : 18th international conference, ICAISC 2019 : Zakopane, June 16–20, 2019 : proceedings, Pt. 1 / eds. Leszek Rutkowski, [et al.]. — Cham : Springer Nature Switzerland AG, cop. 2019. — (Lecture Notes in Computer Science ; ISSN 0302-9743. Lecture Notes in Artificial Intelligence ; LNAI 11508). — ISBN: 978-3-030-20911-7; e-ISBN: 978-3-030-20912-4. — S. 553-560. — Bibliogr. s. 558-560, Abstr. — Publikacja dostępna online od: 2019-05-24
Autorzy (3)
- Baran Mateusz
- AGHSiwik Leszek
- Rzecki Krzysztof
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 123335 |
|---|---|
| Data dodania do BaDAP | 2019-12-09 |
| Tekst źródłowy | URL |
| DOI | 10.1007/978-3-030-20912-4_50 |
| Rok publikacji | 2019 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | International Conference on Artificial Intelligence and Soft Computing 2019 |
| Czasopismo/seria | Lecture Notes in Computer Science |
Abstract
Person identification based on touch screen gestures is a well-known method of authentication in mobile devices. Usually it is only checked if the user entered the correct pattern. Taking into account other biometric data based on the speed and shape of finger movements can provide higher security while the convenience of this authorisation method is not impacted. In this work the application of Sequential Joint Functional Principal Analysis (FPCA) as a dimensionality reduction method for gesture data is explored. Performance of the classifier is measured using 5-fold stratified cross-validation on a set of gestures collected from 12 people. The effects of sampling rate on classification performance is also measured. It is shown that the Support Vector Machine classifier reaches the accuracy of 79% using features obtained using the Sequential Joint FPCA, compared to 70% in the case of Euclidean PCA. © 2019, Springer Nature Switzerland AG.
