The nascent field of mixed reality is seeing an ever-increasing need for user studies and field evaluation, which are particularly challenging given device heterogeneity, diversity of use, and mobile deployment. Immersive analytics tools have recently emerged to support such analysis in situ, yet the complexity of the data also warrants an ex-situ analysis using more traditional non-immersive visual analytics setups. To bridge the gap between both approaches, we introduce ReLive: a mixed-immersion visual analytics framework for exploring and analyzing mixed reality user studies. ReLive combines an in-situ virtual reality view with a complementary ex-situ desktop view. While the virtual reality view allows users to relive interactive spatial recordings replicating the original study, the synchronized desktop view provides a familiar interface for analyzing aggregated data. We validated our concepts in a two-step evaluation consisting of a design walkthrough and an empirical expert user study.
%0 Conference Paper
%1 Hubenschmid2022ReLiv-56817
%A Hubenschmid, Sebastian
%A Wieland, Jonathan
%A Fink, Daniel Immanuel
%A Batch, Andrea
%A Zagermann, Johannes
%A Elmqvist, Niklas
%A Reiterer, Harald
%B CHI Conference on Human Factors in Computing Systems (CHI ’22)
%C New York, NY
%D 2022
%I ACM
%K 2022 c01 from:christinawarren sfbtrr161
%P 1–20
%R 10.1145/3491102.3517550
%T ReLive: Bridging In-Situ and Ex-Situ Visual Analytics for Analyzing Mixed Reality User Studies
%U https://dx.doi.org/10.1145/3491102.3517550
%X The nascent field of mixed reality is seeing an ever-increasing need for user studies and field evaluation, which are particularly challenging given device heterogeneity, diversity of use, and mobile deployment. Immersive analytics tools have recently emerged to support such analysis in situ, yet the complexity of the data also warrants an ex-situ analysis using more traditional non-immersive visual analytics setups. To bridge the gap between both approaches, we introduce ReLive: a mixed-immersion visual analytics framework for exploring and analyzing mixed reality user studies. ReLive combines an in-situ virtual reality view with a complementary ex-situ desktop view. While the virtual reality view allows users to relive interactive spatial recordings replicating the original study, the synchronized desktop view provides a familiar interface for analyzing aggregated data. We validated our concepts in a two-step evaluation consisting of a design walkthrough and an empirical expert user study.
%@ 978-1-4503-9157-3
@inproceedings{Hubenschmid2022ReLiv-56817,
abstract = {The nascent field of mixed reality is seeing an ever-increasing need for user studies and field evaluation, which are particularly challenging given device heterogeneity, diversity of use, and mobile deployment. Immersive analytics tools have recently emerged to support such analysis in situ, yet the complexity of the data also warrants an ex-situ analysis using more traditional non-immersive visual analytics setups. To bridge the gap between both approaches, we introduce ReLive: a mixed-immersion visual analytics framework for exploring and analyzing mixed reality user studies. ReLive combines an in-situ virtual reality view with a complementary ex-situ desktop view. While the virtual reality view allows users to relive interactive spatial recordings replicating the original study, the synchronized desktop view provides a familiar interface for analyzing aggregated data. We validated our concepts in a two-step evaluation consisting of a design walkthrough and an empirical expert user study.},
added-at = {2022-03-16T09:24:36.000+0100},
address = {New York, NY},
author = {Hubenschmid, Sebastian and Wieland, Jonathan and Fink, Daniel Immanuel and Batch, Andrea and Zagermann, Johannes and Elmqvist, Niklas and Reiterer, Harald},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2735cac76f555d39876a20d0025f022c1/sfbtrr161},
booktitle = {CHI Conference on Human Factors in Computing Systems (CHI ’22)},
doi = {10.1145/3491102.3517550},
interhash = {48549b20ae9d7d228662b0865b5fdfcc},
intrahash = {735cac76f555d39876a20d0025f022c1},
isbn = {978-1-4503-9157-3},
keywords = {2022 c01 from:christinawarren sfbtrr161},
pages = {1–20},
publisher = {ACM},
timestamp = {2022-05-17T07:43:32.000+0200},
title = {ReLive: Bridging In-Situ and Ex-Situ Visual Analytics for Analyzing Mixed Reality User Studies},
url = {https://dx.doi.org/10.1145/3491102.3517550},
year = 2022
}