Publications

2025

1. CHI

   

   Ego vs. Exo and Active vs. Passive: Investigating the Effects of Viewpoint and Navigation on Spatial Immersion and Understanding in Immersive Storytelling

   Tao Lu, Qian Zhu , Tiffany Ma , Kam-Kwai Wong , Anlan Xie , Alex Endert , and Yalong Yang

   Proceedings of the CHI Conference on Human Factors in Computing Systems, 2025

   Abs Bib PDF Video

   Visual storytelling combines visuals and narratives to communicate important insights. While web-based visual storytelling is well-established, leveraging the next generation of digital technologies for visual storytelling, specifically immersive technologies, remains underexplored. We investigated the impact of the story viewpoint (from the audience’s perspective) and navigation (when progressing through the story) on spatial immersion and understanding. First, we collected web-based 3D stories and elicited design considerations from three VR developers. We then adapted four selected web-based stories to an immersive format. Finally, we conducted a user study (N=24) to examine egocentric and exocentric viewpoints, active and passive navigation, and the combinations they form. Our results indicated significantly higher preferences for egocentric+active (higher agency and engagement) and exocentric+passive (higher focus on content). We also found a marginal significance of viewpoints on story understanding and a strong significance of navigation on spatial immersion.

   @article{lu2025egoexoactivepassive,
     title = {Ego vs. Exo and Active vs. Passive: Investigating the Effects of Viewpoint and Navigation on Spatial Immersion and Understanding in Immersive Storytelling},
     author = {Lu, Tao and Zhu, Qian and Ma, Tiffany and Wong, Kam-Kwai and Xie, Anlan and Endert, Alex and Yang, Yalong},
     journal = {Proceedings of the CHI Conference on Human Factors in Computing Systems},
     year = {2025},
   }

2024

1. CHI

   

   InteractOut: Leveraging Interaction Proxies as Input Manipulation Strategies for Reducing Smartphone Overuse

   Tao Lu, Hongxiao Zheng , Tianying Zhang , Xuhai Xu , and Anhong Guo

   Proceedings of the CHI Conference on Human Factors in Computing Systems, 2024

   Abs Bib PDF Video

   Smartphone overuse poses risks to people’s physical and mental health. However, current intervention techniques mainly focus on explicitly changing screen content (i.e., output) and often fail to persistently reduce smartphone overuse due to being over-restrictive or over-flexible. We present the design and implementation of InteractOut, a suite of implicit input manipulation techniques that leverage interaction proxies to weakly inhibit the natural execution of common user gestures on mobile devices. We present a design space for input manipulations and demonstrate 8 Android implementations of input interventions. We first conducted a pilot lab study (N=30) to evaluate the usability of these interventions. Based on the results, we then performed a 5-week within-subject field experiment (N=42) to evaluate InteractOut in real-world scenarios. Compared to the traditional and common timed lockout technique, InteractOut significantly reduced the usage time by an additional 15.0% and opening frequency by 17.0% on participant-selected target apps. InteractOut also achieved a 25.4% higher user acceptance rate, and resulted in less frustration and better user experience according to participants’ subjective feedback. InteractOut demonstrates a new direction for smartphone overuse intervention and serves as a strong complementary set of techniques with existing methods.

   @article{lu2024interactout,
     title = {InteractOut: Leveraging Interaction Proxies as Input Manipulation Strategies for Reducing Smartphone Overuse},
     author = {Lu, Tao and Zheng, Hongxiao and Zhang, Tianying and Xu, Xuhai and Guo, Anhong},
     journal = {Proceedings of the CHI Conference on Human Factors in Computing Systems},
     year = {2024},
   }

2. VIS

   

   CompositingVis: Exploring Interactions for Creating Composite Visualizations in Immersive Environments

   Qian Zhu , Tao Lu, Shunan Guo , Xiaojuan Ma , and Yalong Yang

   IEEE Visualization and Visual Analytics, 2024

   Abs Bib PDF

   Composite visualization represents a widely embraced design that combines multiple visual representations to create an integrated view. However, the traditional approach of creating composite visualizations in immersive environments typically occurs asynchronously outside of the immersive space and is carried out by experienced experts. In this work, we aim to empower users to participate in the creation of composite visualization within immersive environments through embodied interactions. This could provide a flexible and fluid experience with immersive visualization and has the potential to facilitate understanding of the relationship between visualization views. We begin with developing a design space of embodied interactions to create various types of composite visualizations with the consideration of data relationships. Drawing inspiration from people’s natural experience of manipulating physical objects, we design interactions \zqbased on the combination of 3D manipulations in immersive environments.Building upon the design space, we present a series of case studies showcasing the interaction to create different kinds of composite visualizations in virtual reality. Subsequently, we conduct a user study to evaluate the usability of the derived interaction techniques and user experience of creating composite visualizations through embodied interactions. We find that empowering users to participate in composite visualizations through embodied interactions enables them to flexibly leverage different visualization views for understanding and communicating the relationships between different views, which underscores the potential of several future application scenarios.

   @article{zhu2024compositingvis,
     title = {CompositingVis: Exploring Interactions for Creating Composite Visualizations in Immersive Environments},
     author = {Zhu, Qian and Lu, Tao and Guo, Shunan and Ma, Xiaojuan and Yang, Yalong},
     journal = {IEEE Visualization and Visual Analytics},
     year = {2024},
     publisher = {IEEE},
   }