Interactive Fixation-to-AOI Mapping for Mobile Eye Tracking Data based on Few-Shot Image Classification
Creators
- 1. German Research Centre for Artificial Intelligence (DFKI); University of Oldenburg
- 2. German Research Centre for Artificial Intelligence (DFKI)
- 3. German Research Centre for Artificial Intelligence (DFKI); University of Stuttgart
Description
Mobile eye tracking is an important tool in psychology and human-centred interaction design for understanding how people process visual scenes and user interfaces. However, analysing recordings from mobile eye trackers, which typically include an egocentric video of the scene and a gaze signal, is a time-consuming and largely manual process. To address this challenge, we propose a web-based annotation tool that leverages few-shot image classification and interactive machine learning (IML) to accelerate the annotation process. The tool allows users to efficiently map fixations to areas of interest (AOI) in a video-editing-style interface. It includes an IML component that generates suggestions and learns from user feedback using a few-shot image classification model initialised with a small number of images per AOI. Our goal is to improve the efficiency and accuracy of fixation-to-AOI mapping in mobile eye tracking.
Files
Barz et al. - 2023 - Interactive Fixation-to-AOI Mapping for Mobile Eye.pdf
Files
(2.7 MB)
Name | Size | Download all |
---|---|---|
md5:3217c7a55070dce8d07a4306d9225d0a
|
2.7 MB | Preview Download |