Department of Computer Science: MSc Thesis Presentation

Matti Mäki-Kihniä will present his MSc thesis "Gender classification based on touch biometrics" on Tuesday 20 April at 16:00 via Zoom.

Gender classification based on touch biometrics

Author: Matti Mäki-Kihniä
Supervisor: Sanna Suoranta

Date: Tuesday 20 April 2021
Time: 16:00
Zoom: (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.

  • Published:
  • Updated: