ABSTRACT
Analysis of human motion data can reveal valuable insights about the utilization of space and interaction of humans with their environment. To support this, we present AvatAR, an immersive analysis environment for the in-situ visualization of human motion data, that combines 3D trajectories with virtual avatars showing people’s detailed movement and posture. Additionally, we describe how visualizations can be embedded directly into the environment, showing what a person looked at or what surfaces they touched, and how the avatar’s body parts can be used to access and manipulate those visualizations. AvatAR combines an AR HMD with a tablet to provide both mid-air and touch interaction for system control, as well as an additional overview device to help users navigate the environment. We implemented a prototype and present several scenarios to show that AvatAR can enhance the analysis of human motion data by making data not only explorable, but experienceable.
Supplemental Material
- Wolfgang Aigner, Silvia Miksch, Wolfgang Müller, Heidrun Schumann, and Christian Tominski. 2008. Visual Methods for Analyzing Time-Oriented Data. IEEE Transactions on Visualization and Computer Graphics 14, 1(2008), 47–60. https://doi.org/10.1109/TVCG.2007.70415Google ScholarDigital Library
- G. Andrienko, N. Andrienko, G. Fuchs, and J. M. C. Garcia. 2018. Clustering Trajectories by Relevant Parts for Air Traffic Analysis. IEEE Transactions on Visualization and Computer Graphics 24, 1 (Jan 2018), 34–44. https://doi.org/10.1109/TVCG.2017.2744322Google ScholarCross Ref
- Gennady Andrienko, Natalia Andrienko, Heidrun Schumann, and Christian Tominski. 2014. Visualization of Trajectory Attributes in Space–Time Cube and Trajectory Wall. Springer Berlin Heidelberg, Berlin, Heidelberg, 157–163. https://doi.org/10.1007/978-3-642-32618-9_11Google ScholarCross Ref
- Natalia Andrienko and Gennady Andrienko. 2013. Visual analytics of movement: An overview of methods, tools and procedures. Information Visualization 12, 1 (2013), 3–24. https://doi.org/10.1177/1473871612457601 arXiv:https://doi.org/10.1177/1473871612457601Google ScholarDigital Library
- Natalia Andrienko, Gennady Andrienko, and Peter Gatalsky. 2003. Exploratory spatio-temporal visualization: an analytical review. Journal of Visual Languages & Computing 14, 6 (2003), 503 – 541. https://doi.org/10.1016/S1045-926X(03)00046-6 Visual Data Mining.Google ScholarCross Ref
- Rahul Arora, Rubaiat Habib Kazi, Tovi Grossman, George Fitzmaurice, and Karan Singh. 2018. SymbiosisSketch: Combining 2D & 3D Sketching for Designing Detailed 3D Objects in Situ. In CHI ’18. ACM, 185:1–185:15. https://doi.org/10.1145/3173574.3173759Google ScholarDigital Library
- Elie Azar and Carol Menassa. 2012. Agent-Based Modeling of Occupants and Their Impact on Energy Use in Commercial Buildings. Journal of Computing in Civil Engineering 26 (07 2012), 506–518. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000158Google ScholarCross Ref
- B. Bach, P. Dragicevic, D. Archambault, C. Hurter, and S. Carpendale. 2014. A Review of Temporal Data Visualizations Based on Space-Time Cube Operations. In EuroVis - STARs, R. Borgo, R. Maciejewski, and I. Viola (Eds.). The Eurographics Association. https://doi.org/10.2312/eurovisstar.20141171Google ScholarCross Ref
- A. Batch, A. Cunningham, M. Cordeil, N. Elmqvist, T. Dwyer, B. H. Thomas, and K. Marriott. 2020. There Is No Spoon: Evaluating Performance, Space Use, and Presence with Expert Domain Users in Immersive Analytics. IEEE Transactions on Visualization and Computer Graphics 26, 1 (Jan 2020), 536–546. https://doi.org/10.1109/TVCG.2019.2934803Google ScholarCross Ref
- Frederik Brudy, Suppachai Suwanwatcharachat, Wenyu Zhang, Steven Houben, and Nicolai Marquardt. 2018. EagleView: A Video Analysis Tool for Visualising and Querying Spatial Interactions of People and Devices. In Proceedings of the 2018 ACM International Conference on Interactive Surfaces and Spaces (Tokyo, Japan) (ISS ’18). Association for Computing Machinery, New York, NY, USA, 61–72. https://doi.org/10.1145/3279778.3279795Google ScholarDigital Library
- Wolfgang Büschel, Anke Lehmann, and Raimund Dachselt. 2021. MIRIA: A Mixed Reality Toolkit for the In-Situ Visualization and Analysis of Spatio-Temporal Interaction Data. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21). ACM, New York, NY, USA, 15 pages. https://doi.org/10.1145/3411764.3445651Google ScholarDigital Library
- Wolfgang Büschel, Annett Mitschick, Thomas Meyer, and Raimund Dachselt. 2019. Investigating Smartphone-Based Pan and Zoom in 3D Data Spaces in Augmented Reality. In Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services (Taipei, Taiwan) (MobileHCI ’19). Association for Computing Machinery, New York, NY, USA, Article 2, 13 pages. https://doi.org/10.1145/3338286.3340113Google ScholarDigital Library
- Wolfgang Büschel, Patrick Reipschläger, Ricardo Langner, and Raimund Dachselt. 2017. Investigating the Use of Spatial Interaction for 3D Data Visualization on Mobile Devices. In Proceedings of the 2017 ACM International Conference on Interactive Surfaces and Spaces (Brighton, United Kingdom) (ISS ’17). ACM, New York, NY, USA, 62–71. https://doi.org/10.1145/3132272.3134125Google ScholarDigital Library
- Stefan Buschmann, Matthias Trapp, and Jürgen Döllner. 2016. Animated visualization of spatial–temporal trajectory data for air-traffic analysis. The Visual Computer 32, 3 (2016), 371–381. https://doi.org/10.1007/s00371-015-1185-9Google ScholarDigital Library
- P. Butcher, N. John, and P. Ritsos. 2021. VRIA: A Web-Based Framework for Creating Immersive Analytics Experiences. IEEE Transactions on Visualization and Computer Graphics 27 (2021), 3213–3225.Google ScholarDigital Library
- Simon Butscher, Sebastian Hubenschmid, Jens Müller, Johannes Fuchs, and Harald Reiterer. 2018. Clusters, Trends, and Outliers: How Immersive Technologies Can Facilitate the Collaborative Analysis of Multidimensional Data. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI ’18). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3173574.3173664Google ScholarDigital Library
- Katy Börner and Shashikant Penumarthy. 2003. Social Diffusion Patterns in Three-Dimensional Virtual Worlds. Information Visualization 2, 3 (2003), 182–198. https://doi.org/10.1057/palgrave.ivs.9500050 arXiv:https://doi.org/10.1057/palgrave.ivs.9500050Google ScholarCross Ref
- Yuanzhi Cao, Tianyi Wang, Xun Qian, Pawan S. Rao, Manav Wadhawan, Ke Huo, and Karthik Ramani. 2019. GhostAR: A Time-Space Editor for Embodied Authoring of Human-Robot Collaborative Task with Augmented Reality. In Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology (New Orleans, LA, USA) (UIST ’19). Association for Computing Machinery, New York, NY, USA, 521–534. https://doi.org/10.1145/3332165.3347902Google ScholarDigital Library
- Zhe Cao, Hang Gao, Karttikeya Mangalam, Qizhi Cai, Minh Vo, and Jitendra Malik. 2020. Long-term human motion prediction with scene context. In ECCV.Google Scholar
- Zhe Cao, Tomas Simon, Shih-En Wei, and Yaser Sheikh. 2017. Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).Google ScholarCross Ref
- M. Cavallo, M. Dholakia, M. Havlena, K. Ocheltree, and M. Podlaseck. 2019. Dataspace: A Reconfigurable Hybrid Reality Environment for Collaborative Information Analysis. In IEEE VR ’19. 145–153. https://doi.org/10.1109/VR.2019.8797733Google ScholarCross Ref
- Marco Cavallo, Mishal Dolakia, Matous Havlena, Kenneth Ocheltree, and Mark Podlaseck. 2019. Immersive Insights: A Hybrid Analytics System ForCollaborative Exploratory Data Analysis. In 25th ACM Symposium on Virtual Reality Software and Technology (Parramatta, NSW, Australia) (VRST ’19). Association for Computing Machinery, New York, NY, USA, Article 9, 12 pages. https://doi.org/10.1145/3359996.3364242Google ScholarDigital Library
- Maxime Cordeil, Andrew Cunningham, Tim Dwyer, Bruce H. Thomas, and Kim Marriott. 2017. ImAxes: Immersive Axes As Embodied Affordances for Interactive Multivariate Data Visualisation. In UIST ’17. ACM, 71–83. https://doi.org/10.1145/3126594.3126613Google ScholarDigital Library
- Haoran Dai, Yubo Tao, and Hai Lin. 2020. Visual analytics of urban transportation from a bike-sharing and taxi perspective. Journal of Visualization 23, 6 (2020), 1053–1070. https://doi.org/10.1007/s12650-020-00673-8Google ScholarDigital Library
- Philip DeCamp, George Shaw, Rony Kubat, and Deb Roy. 2010. An Immersive System for Browsing and Visualizing Surveillance Video. In Proceedings of the 18th ACM International Conference on Multimedia (Firenze, Italy) (MM ’10). Association for Computing Machinery, New York, NY, USA, 371–380. https://doi.org/10.1145/1873951.1874002Google ScholarDigital Library
- Tim Dwyer, Kim Marriott, Tobias Isenberg, Karsten Klein, Nathalie Riche, Falk Schreiber, Wolfgang Stuerzlinger, and Bruce H. Thomas. 2018. Immersive Analytics: An Introduction. Springer, 1–23. https://doi.org/10.1007/978-3-030-01388-2_1Google ScholarCross Ref
- Matteo Fabbri, Fabio Lanzi, Simone Calderara, Andrea Palazzi, Roberto Vezzani, and Rita Cucchiara. 2018. Learning to Detect and Track Visible and Occluded Body Joints in a Virtual World. In European Conference on Computer Vision (ECCV).Google ScholarDigital Library
- J. A. W. Filho, W. Stuerzlinger, and L. Nedel. 2020. Evaluating an Immersive Space-Time Cube Geovisualization for Intuitive Trajectory Data Exploration. IEEE Transactions on Visualization and Computer Graphics 26, 1 (Jan 2020), 514–524. https://doi.org/10.1109/TVCG.2019.2934415Google ScholarCross Ref
- H. Guo, Z. Wang, B. Yu, H. Zhao, and X. Yuan. 2011. TripVista: Triple Perspective Visual Trajectory Analytics and its application on microscopic traffic data at a road intersection. In 2011 IEEE Pacific Visualization Symposium. 163–170. https://doi.org/10.1109/PACIFICVIS.2011.5742386Google ScholarCross Ref
- N. Hoobler, G. Humphreys, and M. Agrawala. 2004. Visualizing competitive behaviors in multi-user virtual environments. In IEEE Visualization 2004. 163–170. https://doi.org/10.1109/VISUAL.2004.120Google ScholarDigital Library
- Sebastian Hubenschmid, Johannes Zagermann, Simon Butscher, and Harald Reiterer. 2021. STREAM: Exploring the Combination of Spatially-Aware Tablets with Augmented Reality Head-Mounted Displays for Immersive Analytics. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3411764.3445298Google ScholarDigital Library
- Hanbyul Joo, Tomas Simon, Xulong Li, Hao Liu, Lei Tan, Lin Gui, Sean Banerjee, Timothy Scott Godisart, Bart Nabbe, Iain Matthews, Takeo Kanade, Shohei Nobuhara, and Yaser Sheikh. 2017. Panoptic Studio: A Massively Multiview System for Social Interaction Capture. IEEE Transactions on Pattern Analysis and Machine Intelligence (2017).Google Scholar
- Daniel Kepplinger, Günter Wallner, Simone Kriglstein, and Michael Lankes. 2020. See, Feel, Move: Player Behaviour Analysis through Combined Visualization of Gaze, Emotions, and Movement. Association for Computing Machinery, New York, NY, USA, 1–14. https://doi.org/10.1145/3313831.3376401Google ScholarDigital Library
- Simon Kloiber, Volker Settgast, Christoph Schinko, Martin Weinzerl, Johannes Fritz, Tobias Schreck, and Reinhold Preiner. 2020. Immersive analysis of user motion in VR applications. The Visual Computer 36, 10 (2020), 1937–1949. https://doi.org/10.1007/s00371-020-01942-1Google ScholarDigital Library
- M. Kraus, T. Pollok, M. Miller, T. Kilian, T. Moritz, D. Schweitzer, J. Beyerer, D. Keim, C. Qu, and W. Jentner. 2020. Toward Mass Video Data Analysis: Interactive and Immersive 4D Scene Reconstruction.. In Sensor, Vol. 20. https://doi.org/10.3390/s20185426Google ScholarCross Ref
- D. Lange, F. Samsel, I. Karamouzas, S. J. Guy, R. Dockter, T. Kowalewski, and D. F. Keefe. 2017. Trajectory Mapper: Interactive Widgets and Artist-Designed Encodings for Visualizing Multivariate Trajectory Data. In Proceedings of the Eurographics/IEEE VGTC Conference on Visualization: Short Papers (Barcelona, Spain) (EuroVis ’17). Eurographics Association, Goslar, DEU, 103–107. https://doi.org/10.2312/eurovisshort.20171141Google ScholarDigital Library
- Ricardo Langner, Marc Satkowski, Wolfgang Büschel, and Raimund Dachselt. 2021. MARVIS: Combining Mobile Devices and Augmented Reality for Visual Data Analysis. In Proceedings of the 2021 ACM Conference on Human Factors in Computing Systems (Yokohama, Japan). ACM, New York, NY, USA, 17 pages. https://doi.org/10.1145/3411764.3445593Google ScholarDigital Library
- Joel Lanir, Tsvi Kuflik, Julia Sheidin, Nisan Yavin, Kate Leiderman, and Michael Segal. 2017. Visualizing museum visitors’ behavior: Where do they go and what do they do there?Personal and Ubiquitous Computing 21 (04 2017). https://doi.org/10.1007/s00779-016-0994-9Google ScholarDigital Library
- Bokyung Lee, Michael Lee, Pan Zhang, Alexander Tessier, and Azam Khan. 2019. Semantic Human Activity Annotation Tool Using Skeletonized Surveillance Videos. In Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers (London, United Kingdom) (UbiComp/ISWC ’19 Adjunct). Association for Computing Machinery, New York, NY, USA, 312–315. https://doi.org/10.1145/3341162.3343807Google ScholarDigital Library
- Klemen Lilija, Henning Pohl, and Kasper Hornbæk. 2020. Who Put That There? Temporal Navigation of Spatial Recordings by Direct Manipulation. Association for Computing Machinery, New York, NY, USA, 1–11. https://doi.org/10.1145/3313831.3376604Google ScholarDigital Library
- Tahir Mahmood, Willis Fulmer, Neelesh Mungoli, Jian Huang, and Aidong Lu. 2019. Improving Information Sharing and Collaborative Analysis for Remote GeoSpatial Visualization Using Mixed Reality. In 2019 IEEE International Symposium on Mixed and Augmented Reality (ISMAR). 236–247. https://doi.org/10.1109/ISMAR.2019.00021Google ScholarCross Ref
- Nicolai Marquardt, Frederico Schardong, and Anthony Tang. 2015. EXCITE: EXploring Collaborative Interaction in Tracked Environments. In Human-Computer Interaction – INTERACT 2015, Julio Abascal, Simone Barbosa, Mirko Fetter, Tom Gross, Philippe Palanque, and Marco Winckler (Eds.). Springer International Publishing, Cham, 89–97.Google Scholar
- Dushyant Mehta, Oleksandr Sotnychenko, Franziska Mueller, Weipeng Xu, Srinath Sridhar, Gerard Pons-Moll, and Christian Theobalt. 2018. Single-Shot Multi-Person 3D Pose Estimation From Monocular RGB. In 3D Vision (3DV), 2018 Sixth International Conference on. IEEE. http://gvv.mpi-inf.mpg.de/projects/SingleShotMultiPersonGoogle Scholar
- Dinara Moura, Magy Seif el Nasr, and Christopher D. Shaw. 2011. Visualizing and Understanding Players’ Behavior in Video Games: Discovering Patterns and Supporting Aggregation and Comparison. In Proceedings of the 2011 ACM SIGGRAPH Symposium on Video Games (Vancouver, British Columbia, Canada) (Sandbox ’11). Association for Computing Machinery, New York, NY, USA, 11–15. https://doi.org/10.1145/2018556.2018559Google ScholarDigital Library
- A. Nakazawa, S. Nakaoka, T. Shiratori, and K. Ikeuchi. 2003. Analysis and synthesis of human dance motions. In Proceedings of IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI2003.83–88. https://doi.org/10.1109/MFI-2003.2003.1232637Google ScholarCross Ref
- Michael Nebeling, Maximilian Speicher, Xizi Wang, Shwetha Rajaram, Brian D. Hall, Zijian Xie, Alexander R. E. Raistrick, Michelle Aebersold, Edward G. Happ, Jiayin Wang, Yanan Sun, Lotus Zhang, Leah E. Ramsier, and Rhea Kulkarni. 2020. MRAT: The Mixed Reality Analytics Toolkit. Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3313831.3376330Google ScholarDigital Library
- Michael Oppermann and Tamara Munzner. 2020. Ocupado: Visualizing Location-Based Counts Over Time Across Buildings. Comput. Graph. Forum 39, 3 (2020), 127–138. https://doi.org/10.1111/cgf.13968Google ScholarCross Ref
- Patrick Reipschläger, Tamara Flemisch, and Raimund Dachselt. 2021. Personal Augmented Reality for Information Visualization on Large Interactive Displays. IEEE Transactions on Visualization and Computer Graphics 27 (2 2021), 1182–1192. Issue 2. https://doi.org/10.1109/TVCG.2020.3030460Google ScholarCross Ref
- René Rosenbaum, Jeremy Bottleson, Zhuiguang Liu, and Bernd Hamann. 2011. Involve Me and I Will Understand!–Abstract Data Visualization in Immersive Environments. In Advances in Visual Computing, George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Song Wang, Kim Kyungnam, Bedrich Benes, Kenneth Moreland, Christoph Borst, Stephen DiVerdi, Chiang Yi-Jen, and Jiang Ming (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 530–540.Google Scholar
- D. Sacha, F. Al-Masoudi, M. Stein, T. Schreck, D. A. Keim, G. Andrienko, and H. Janetzko. 2017. Dynamic Visual Abstraction of Soccer Movement. Computer Graphics Forum 36, 3 (2017), 305–315. https://doi.org/10.1111/cgf.13189 arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1111/cgf.13189Google ScholarDigital Library
- Michael Saenz, Ali Baigelenov, Ya-Hsin Hung, and Paul Parsons. 2017. Reexamining the cognitive utility of 3D visualizations using augmented reality holograms. In IEEE VIS Workshop on Immersive Analytics: Exploring Future Interaction and Visualization Technologies for Data Analytics.Google Scholar
- D. Schmalstieg, A. Fuhrmann, and G. Hesina. 2000. Bridging multiple user interface dimensions with augmented reality. In Proceedings IEEE and ACM International Symposium on Augmented Reality (ISAR 2000). 20–29. https://doi.org/10.1109/ISAR.2000.880919Google ScholarCross Ref
- Mickael Sereno, Lonni Besançon, and Tobias Isenberg. 2019. Supporting Volumetric Data Visualization and Analysis by Combining Augmented Reality Visuals with Multi-Touch Input. In EuroVis ’19 - Posters. https://doi.org/10.2312/eurp.20191136Google ScholarCross Ref
- Tomas Simon, Hanbyul Joo, Iain Matthews, and Yaser Sheikh. 2017. Hand Keypoint Detection in Single Images using Multiview Bootstrapping. In CVPR.Google Scholar
- Tomas Simon, Hanbyul Joo, and Yaser Sheikh. 2017. Hand Keypoint Detection in Single Images using Multiview Bootstrapping. CVPR (2017).Google Scholar
- S. Y. Ssin, J. A. Walsh, R. T. Smith, A. Cunningham, and B. H. Thomas. 2019. GeoGate: Correlating Geo-Temporal Datasets Using an Augmented Reality Space-Time Cube and Tangible Interactions. In 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR). 210–219. https://doi.org/10.1109/VR.2019.8797812Google ScholarCross Ref
- Zsolt Szalavári and Michael Gervautz. 1997. The Personal Interaction Panel – a Two-Handed Interface for Augmented Reality. Computer Graphics Forum 16, 3 (1997), C335–C346. https://doi.org/10.1111/1467-8659.00137 arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1111/1467-8659.00137Google ScholarCross Ref
- Anthony Tang, Michel Pahud, Sheelagh Carpendale, and Bill Buxton. 2010. VisTACO: Visualizing Tabletop Collaboration. In ACM International Conference on Interactive Tabletops and Surfaces (Saarbrücken, Germany) (ITS ’10). Association for Computing Machinery, New York, NY, USA, 29–38. https://doi.org/10.1145/1936652.1936659Google ScholarDigital Library
- C. Tominski, H. Schumann, G. Andrienko, and N. Andrienko. 2012. Stacking-Based Visualization of Trajectory Attribute Data. IEEE Transactions on Visualization and Computer Graphics 18, 12 (Dec 2012), 2565–2574. https://doi.org/10.1109/TVCG.2012.265Google ScholarDigital Library
- Timo von Marcard, Roberto Henschel, Michael Black, Bodo Rosenhahn, and Gerard Pons-Moll. 2018. Recovering Accurate 3D Human Pose in The Wild Using IMUs and a Moving Camera. In European Conference on Computer Vision (ECCV).Google ScholarDigital Library
- Ulrich von Zadow and Raimund Dachselt. 2017. GIAnT: Visualizing Group Interaction at Large Wall Displays. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, 2639–2647. https://doi.org/10.1145/3025453.3026006Google ScholarDigital Library
- J. A. Wagner Filho, M. F. Rey, C. M. D. S. Freitas, and L. Nedel. 2018. Immersive Visualization of Abstract Information: An Evaluation on Dimensionally-Reduced Data Scatterplots. In 2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR). 483–490. https://doi.org/10.1109/VR.2018.8447558Google ScholarCross Ref
- J. A. Walsh, J. Zucco, R. T. Smith, and B. H. Thomas. 2016. Temporal-Geospatial Cooperative Visual Analysis. In 2016 Big Data Visual Analytics (BDVA). 1–8. https://doi.org/10.1109/BDVA.2016.7787050Google ScholarCross Ref
- Ji Soo Yi, Youn ah Kang, John Stasko, and J.A. Jacko. 2007. Toward a Deeper Understanding of the Role of Interaction in Information Visualization. IEEE Transactions on Visualization and Computer Graphics 13, 6 (Nov 2007), 1224–1231. https://doi.org/10.1109/TVCG.2007.70515Google ScholarDigital Library
- Xingyao Yu, Katrin Angerbauer, Peter Mohr, Denis Kalkofen, and Michael Sedlmair. 2020. Perspective Matters: Design Implications for Motion Guidance in Mixed Reality. In 2020 IEEE International Symposium on Mixed and Augmented Reality (ISMAR). 577–587. https://doi.org/10.1109/ISMAR50242.2020.00085Google ScholarCross Ref
- Meng-Jia Zhang, Jie Li, and Kang Zhang. 2015. Using Virtual Reality Technique to Enhance Experience of Exploring 3D Trajectory Visualizations. In Proceedings of the 8th International Symposium on Visual Information Communication and Interaction (Tokyo, AA, Japan) (VINCI ’15). Association for Computing Machinery, New York, NY, USA, 168–169. https://doi.org/10.1145/2801040.2801072Google ScholarDigital Library
Index Terms
- AvatAR: An Immersive Analysis Environment for Human Motion Data Combining Interactive 3D Avatars and Trajectories
Recommendations
Immersive analysis of user motion in VR applications
AbstractWith the rise of virtual reality experiences for applications in entertainment, industry, science and medicine, the evaluation of human motion in immersive environments is becoming more important. By analysing the motion of virtual reality users, ...
Pearl: Physical Environment based Augmented Reality Lenses for In-Situ Human Movement Analysis
CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing SystemsThis paper presents Pearl, a mixed-reality approach for the analysis of human movement data in situ. As the physical environment shapes human motion and behavior, the analysis of such motion can benefit from the direct inclusion of the environment in the ...
DeAR: Combining Desktop and Augmented Reality for Visual Data Analysis
SVR '23: Proceedings of the 25th Symposium on Virtual and Augmented RealityCombining different interfaces and displays might enhance the capabilities of data analysis, particularly in the context of Immersive Analytics. In this work, we design a prototype, called DeAR (Combining Desktop and Augmented Reality for Visual Data ...
Comments