We report on an interdisciplinary visual analytics project wherein
automotive engineers analyze test drive videos. These videos are
annotated with navigation-specific augmented reality (AR) content, and the engineers need to identify issues and evaluate the
behavior of the underlying AR navigation system. With the increasing amount of video data, traditional analysis approaches can no
longer be conducted in an acceptable timeframe. To address this
issue, we collaboratively developed Caarvida, a visual analytics tool
that helps engineers to accomplish their tasks faster and handle an
increased number of videos. Caarvida combines automatic video
analysis with interactive and visual user interfaces. We conducted
two case studies which show that Caarvida successfully supports
domain experts and speeds up their task completion time.
%0 Conference Paper
%1 achberger2020caarvida
%A Achberger, Alexander
%A Cutura, René
%A Türksoy, Oguzhan
%A Sedlmair, Michael
%B Proceedings of the International Conference on Advanced Visual Interfaces
%D 2020
%K myown vis(us) visus visus:achberar visus:cuturare visus:sedlmaml
%P 1--9
%R 10.1145/3399715.3399862
%T Caarvida: Visual Analytics for Test Drive Videos
%U https://doi.org/10.1145/3399715.3399862
%X We report on an interdisciplinary visual analytics project wherein
automotive engineers analyze test drive videos. These videos are
annotated with navigation-specific augmented reality (AR) content, and the engineers need to identify issues and evaluate the
behavior of the underlying AR navigation system. With the increasing amount of video data, traditional analysis approaches can no
longer be conducted in an acceptable timeframe. To address this
issue, we collaboratively developed Caarvida, a visual analytics tool
that helps engineers to accomplish their tasks faster and handle an
increased number of videos. Caarvida combines automatic video
analysis with interactive and visual user interfaces. We conducted
two case studies which show that Caarvida successfully supports
domain experts and speeds up their task completion time.
@inproceedings{achberger2020caarvida,
abstract = {We report on an interdisciplinary visual analytics project wherein
automotive engineers analyze test drive videos. These videos are
annotated with navigation-specific augmented reality (AR) content, and the engineers need to identify issues and evaluate the
behavior of the underlying AR navigation system. With the increasing amount of video data, traditional analysis approaches can no
longer be conducted in an acceptable timeframe. To address this
issue, we collaboratively developed Caarvida, a visual analytics tool
that helps engineers to accomplish their tasks faster and handle an
increased number of videos. Caarvida combines automatic video
analysis with interactive and visual user interfaces. We conducted
two case studies which show that Caarvida successfully supports
domain experts and speeds up their task completion time.},
added-at = {2021-12-09T10:50:28.000+0100},
author = {Achberger, Alexander and Cutura, René and Türksoy, Oguzhan and Sedlmair, Michael},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/25f33ce82da0f0b2dfe5ec03360fe265a/aachberger},
booktitle = {Proceedings of the International Conference on Advanced Visual Interfaces},
doi = {10.1145/3399715.3399862},
interhash = {e58bf41fa2a702474a61ce6ad7fdf55f},
intrahash = {5f33ce82da0f0b2dfe5ec03360fe265a},
keywords = {myown vis(us) visus visus:achberar visus:cuturare visus:sedlmaml},
pages = {1--9},
timestamp = {2021-12-09T09:50:28.000+0100},
title = {Caarvida: Visual Analytics for Test Drive Videos},
url = {https://doi.org/10.1145/3399715.3399862},
year = 2020
}