Department of Computer Science: MSc Thesis Presentation
Gender classification based on touch biometrics
Author: Matti Mäki-Kihniä
Supervisor: Sanna Suoranta
Date: Tuesday 20 April 2021
Zoom: https://aalto.zoom.us/j/69943801958 (passcode: 365778)
The Android operating system offers fine-grained APIs to capture users' touch events, the exposed touch data has been used for user authentication as well as in classification of different soft-biometrics. This thesis analyses whether data gathered from a 2048 game can be used for gender classification. A dataset of 260,000 touch gestures from 66 different users is analyzed and the results compared to related research.