SFB/Transregio 161 "Quantitative Methods for Visual Computing"

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3,631 to 3,640 of 3,690 Results

Proxemics for Human-Agent Interaction in Augmented Reality Mar 8, 2022 - SFB-TRR 161 C06 "User-Adaptive Mixed Reality" Huang, Ann; Knierim, Pascal; Chiossi, Francesco; Chuang, Lewis; Welsch, Robin, 2022, "Proxemics for Human-Agent Interaction in Augmented Reality", https://doi.org/10.18419/DARUS-2525, DaRUS, V1, UNF:6:gMC1ZC3kIcnTw0ymCcJbgQ== [fileUNF] We report an experiment (N=54) where participants interacted with agents in an AR (Augmented Reality) art gallery scenario. When participants approached six virtual agents (i.e., two males, two females, a humanoid robot, and a pillar) to ask for directions, we found that participants respected the agents’ PS (Personal Space) and modulated interpers...
df_holo_electrodermal_activity_analysis.tab Mar 8, 2022 - Proxemics for Human-Agent Interaction in Augmented Reality Tabular Data - 37.0 KB - 7 Variables, 540 Observations - UNF:6:zLLTaoJyI4/oSsqd1A78/g== Dataframe with Electrodermal Activity (EDA) Data
df_holo_min.tab Mar 8, 2022 - Proxemics for Human-Agent Interaction in Augmented Reality Tabular Data - 129.5 KB - 13 Variables, 1068 Observations - UNF:6:1BTACawKEQZOICjP20Y7yw== Dataframe with minimum/passing distances of each participant
df_holo.tab Mar 8, 2022 - Proxemics for Human-Agent Interaction in Augmented Reality Tabular Data - 112.3 KB - 13 Variables, 926 Observations - UNF:6:UXU37lC46OcL0ZjIEAzlRA== Dataframe with each participant's preferred IPD, as well as passing distances with respect to each virtual agent (separated by sex) on each trial for both experimental blocks
Inference_CHI22_2.R Mar 8, 2022 - Proxemics for Human-Agent Interaction in Augmented Reality R Syntax - 9.7 KB - MD5: 4fe9f0ea8b83f11c078b34baa0079992 Data analysis Code
like_data.tab Mar 8, 2022 - Proxemics for Human-Agent Interaction in Augmented Reality Tabular Data - 2.7 KB - 3 Variables, 252 Observations - UNF:6:PP1EuYfA1WaWRDaJj4iRBA== Dataframe with Likeability Data. Participants' responses for the likeability of the virtual agents recorded on a 5 point Likert-Scale: 1 = "I strongly dislike the agent"; 5 = "I strongly like the agent"
Questionnaire_Demographics_Data_r2.tab Mar 8, 2022 - Proxemics for Human-Agent Interaction in Augmented Reality Tabular Data - 978 B - 4 Variables, 54 Observations - UNF:6:KI4Fyb6PjhJNuL7/Y10ARQ== Dataframe with demographics data.
vote_perceived_gender.tab Mar 8, 2022 - Proxemics for Human-Agent Interaction in Augmented Reality Tabular Data - 4.4 KB - 7 Variables, 51 Observations - UNF:6:0Pmp+AHdf7fH9Gdom/V4Dg== Dataframe with perceived gender. Column names "F1", "F2", "M1", "M2", "robot", "Pillar" correspond to the name of the virtual agents used in the study. The order and their appearances are the same as Figure 2 in the manuscript. F1 stands for "Female 1"; F2 stands for "Female 2"; M1 stands for "Male 1", M2 stands for "Male 2". The folder contains t...
SFB-TRR 161 B05 "Efficient Large Scale Variational 3D Reconstruction"(Universität Konstanz) Dec 16, 2021 The central goal of the project is to research and develop high-performance variational methods for large scale 3D reconstruction problems, which are general and accurate while meeting computation time constraints imposed by visual computing applications.
SFB-TRR 161 A04 "Quantitative Models for Visual Abstraction"(Universität Konstanz) Dec 16, 2021

Proxemics for Human-Agent Interaction in Augmented Reality

Mar 8, 2022 - SFB-TRR 161 C06 "User-Adaptive Mixed Reality"

Huang, Ann; Knierim, Pascal; Chiossi, Francesco; Chuang, Lewis; Welsch, Robin, 2022, "Proxemics for Human-Agent Interaction in Augmented Reality", https://doi.org/10.18419/DARUS-2525, DaRUS, V1, UNF:6:gMC1ZC3kIcnTw0ymCcJbgQ== [fileUNF]

We report an experiment (N=54) where participants interacted with agents in an AR (Augmented Reality) art gallery scenario. When participants approached six virtual agents (i.e., two males, two females, a humanoid robot, and a pillar) to ask for directions, we found that participants respected the agents’ PS (Personal Space) and modulated interpers...

df_holo_electrodermal_activity_analysis.tab

Mar 8, 2022 - Proxemics for Human-Agent Interaction in Augmented Reality

Tabular Data - 37.0 KB - 7 Variables, 540 Observations -

Dataframe with Electrodermal Activity (EDA) Data

df_holo_min.tab

Mar 8, 2022 - Proxemics for Human-Agent Interaction in Augmented Reality

Tabular Data - 129.5 KB - 13 Variables, 1068 Observations -

Dataframe with minimum/passing distances of each participant

df_holo.tab

Mar 8, 2022 - Proxemics for Human-Agent Interaction in Augmented Reality

Tabular Data - 112.3 KB - 13 Variables, 926 Observations -

Dataframe with each participant's preferred IPD, as well as passing distances with respect to each virtual agent (separated by sex) on each trial for both experimental blocks

Inference_CHI22_2.R

Mar 8, 2022 - Proxemics for Human-Agent Interaction in Augmented Reality

R Syntax - 9.7 KB -

Data analysis Code

like_data.tab

Mar 8, 2022 - Proxemics for Human-Agent Interaction in Augmented Reality

Tabular Data - 2.7 KB - 3 Variables, 252 Observations -

Dataframe with Likeability Data. Participants' responses for the likeability of the virtual agents recorded on a 5 point Likert-Scale: 1 = "I strongly dislike the agent"; 5 = "I strongly like the agent"

Questionnaire_Demographics_Data_r2.tab

Mar 8, 2022 - Proxemics for Human-Agent Interaction in Augmented Reality

Tabular Data - 978 B - 4 Variables, 54 Observations -

Dataframe with demographics data.

vote_perceived_gender.tab

Mar 8, 2022 - Proxemics for Human-Agent Interaction in Augmented Reality

Tabular Data - 4.4 KB - 7 Variables, 51 Observations -

Dataframe with perceived gender. Column names "F1", "F2", "M1", "M2", "robot", "Pillar" correspond to the name of the virtual agents used in the study. The order and their appearances are the same as Figure 2 in the manuscript. F1 stands for "Female 1"; F2 stands for "Female 2"; M1 stands for "Male 1", M2 stands for "Male 2". The folder contains t...

SFB-TRR 161 B05 "Efficient Large Scale Variational 3D Reconstruction"(Universität Konstanz)

Dec 16, 2021

The central goal of the project is to research and develop high-performance variational methods for large scale 3D reconstruction problems, which are general and accurate while meeting computation time constraints imposed by visual computing applications.

SFB-TRR 161 A04 "Quantitative Models for Visual Abstraction"(Universität Konstanz)

Dec 16, 2021

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