Visual Analytics and Annotation of Pervasive Eye Tracking Video
Kuno Kurzhals, Nils Rodrigues, Maurice Koch, Michael Stoll, Andrés Bruhn, Andreas Bulling, Daniel Weiskopf
Proc. ACM International Symposium on Eye Tracking Research and Applications (ETRA), pp. 1-9, 2020.
Visual interface for annotation and analysis: the multi-layered timeline shows feature intensities over time for respective time spans. Gaze and video parameters allow analysts to refine query results, supported by visual guidance. The query results are represented by thumbnails of respective time spans that are animated on mouse over.
Abstract
We propose a new technique for visual analytics and annotation of long-term pervasive eye tracking data for which a combined analysis of gaze and egocentric video is necessary. Our approach enables two important tasks for such data for hour-long videos from individual participants: (1) efficient annotation and (2) direct interpretation of the results. Exemplary time spans can be selected by the user and are then used as a query that initiates a fuzzy search of similar time spans based on gaze and video features. In an iterative refinement loop, the query interface then provides suggestions for the importance of individual features to improve the search results. A multi-layered timeline visualization shows an overview of annotated time spans. We demonstrate the efficiency of our approach for analyzing activities in about seven hours of video in a case study and discuss feedback on our approach from novices and experts performing the annotation task.Links
Paper: kurzhals20_etra.pdf
BibTeX
@inproceedings{kurzhals20_etra,
title = {Visual Analytics and Annotation of Pervasive Eye Tracking Video},
author = {Kurzhals, Kuno and Rodrigues, Nils and Koch, Maurice and Stoll, Michael and Bruhn, Andrés and Bulling, Andreas and Weiskopf, Daniel},
year = {2020},
booktitle = {Proc. ACM International Symposium on Eye Tracking Research and Applications (ETRA)},
doi = {10.1145/3379155.3391326},
pages = {1-9}
}
