PLUME: Record, Replay, Analyze and Share User Behavior in 6DoF XR Experiences

被引:2
作者
Javerliat, Charles [1 ]
Villenave, Sophie [1 ]
Raimbaud, Pierre [1 ]
Lavoue, Guillaume [1 ]
机构
[1] Ecole Cent Lyon, CNRS, ENISE, LIRIS UMR5025, Ecully, France
关键词
Behavioral sciences; Physiology; Three-dimensional displays; X reality; Visualization; Trajectory; Data visualization; Extended Reality; Virtual Reality; User Behavior; Human-Computer Interaction; Quality of Experience; Data Collection; Physiological Signals; VIRTUAL-REALITY; SICKNESS; TRACKING;
D O I
10.1109/TVCG.2024.3372107
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
From education to medicine to entertainment, a wide range of industrial and academic fields now utilize eXtended Reality (XR) technologies. This diversity and growing use are boosting research and leading to an increasing number of XR experiments involving human subjects. The main aim of these studies is to understand the user experience in the broadest sense, such as the user cognitive and emotional states. Behavioral data collected during XR experiments, such as user movements, gaze, actions, and physiological signals constitute precious assets for analyzing and understanding the user experience. While they contribute to overcome the intrinsic flaws of explicit data such as post-experiment questionnaires, the required acquisition and analysis tools are costly and challenging to develop, especially for 6DoF (Degrees of Freedom) XR experiments. Moreover, there is no common format for XR behavioral data, which restrains data-sharing, and thus hinders wide usages across the community, replicability of studies, and the constitution of large datasets or meta-analysis. In this context, we present PLUME, an open-source software toolbox (PLUME Recorder, PLUME Viewer, PLUME Python) that allows for the exhaustive record of XR behavioral data (including synchronous physiological signals), their offline interactive replay and analysis (with a standalone application), and their easy sharing due to our compact and interoperable data format. We believe that PLUME can greatly benefit the scientific community by making the use of behavioral and physiological data available for the greatest, contributing to the reproducibility and replicability of XR user studies, enabling the creation of large datasets, and contributing to a deeper understanding of user experience.
引用
收藏
页码:2087 / 2097
页数:11
相关论文
共 80 条
  • [51] MoBILAB: an open source toolbox for analysis and visualization of mobile brain/body imaging data
    Ojeda, Alejandro
    Bigdely-Shamlo, Nima
    Makeig, Scott
    [J]. FRONTIERS IN HUMAN NEUROSCIENCE, 2014, 8
  • [52] Pfeiffer T., 2012, P S EYE TRACKING RES, P29, DOI [DOI 10.1145/2168556.2168560, 10.1145/2168556.2168560]
  • [53] Model-based Real-time Visualization of Realistic Three-Dimensional Heat Maps for Mobile Eye Tracking and Eye Tracking in Virtual Reality
    Pfeiffer, Thies
    Memile, Cem
    [J]. 2016 ACM SYMPOSIUM ON EYE TRACKING RESEARCH & APPLICATIONS (ETRA 2016), 2016, : 95 - 102
  • [54] Raimbaud P., 2020, PhD thesis, P3
  • [55] The Stare-in-the-Crowd Effect When Navigating a Crowd in Virtual Reality
    Raimbaud, Pierre
    Jovane, Alberto
    Zibrek, Katja
    Pacchierotti, Claudio
    Christie, Marc
    Hoyet, Ludovic
    Pettre, Julien
    Olivier, Anne-Helene
    [J]. PROCEEDINGS OF THE ACM SYMPOSIUM ON APPLIED PERCEPTION, SAP 2023, 2023,
  • [56] AvatAR: An Immersive Analysis Environment for Human Motion Data Combining Interactive 3D Avatars and Trajectories
    Reipschlaeger, Patrick
    Brudy, Frederik
    Dachselt, Raimund
    Matejka, Justin
    Fitzmaurice, George
    Anderson, Fraser
    [J]. PROCEEDINGS OF THE 2022 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI' 22), 2022,
  • [57] Rennes I., Virtual Crowds! CrowdMP is a Unity project used as an exper imentation platform
  • [58] An Integrated Framework for Understanding Multimodal Embodied Experiences in Interactive Virtual Reality
    Robert, Florent
    Wu, Hui-Yin
    Sassatelli, Lucile
    Ramanoel, Stephen
    Gros, Auriane
    Winckler, Marco
    [J]. PROCEEDINGS OF THE 2023 ACM INTERNATIONAL CONFERENCE ON INTERACTIVE MEDIA EXPERIENCES, IMX 2023, 2023, : 14 - 26
  • [59] Extending 3-DoF metrics to model user behaviour similarity in 6-DoF immersive applications
    Rossi, Silvia
    Viola, Irene
    Toni, Laura
    Cesar, Pablo
    [J]. PROCEEDINGS OF THE 2023 PROCEEDINGS OF THE 14TH ACM MULTIMEDIA SYSTEMS CONFERENCE, MMSYS 2023, 2023, : 39 - 50
  • [60] Construction of the Virtual Embodiment Questionnaire (VEQ)
    Roth, Daniel
    Latoschik, Marc Erich
    [J]. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2020, 26 (12) : 3546 - 3556