Ananya Ipsita

dblp:264/7491 · DBLP profile ↗
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4ranked-venue papers
1as first author
3since 2021 · last 2022
0000-0002-2588-9833ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 4 · 1 first-author · 3 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021
YearPublicationVenuePosition
2022 Towards Modeling of Virtual Reality Welding Simulators to Promote Accessible and Scalable Training
abstract
The US manufacturing industry is currently facing a welding workforce shortage which is largely due to inadequacy of widespread welding training. To address this challenge, we present a Virtual Reality (VR)-based training system aimed at transforming state-of-the-art-welding simulations and in-person instruction into a widely accessible and engaging platform. We applied backward design principles to design a low-cost welding simulator in the form of modularized units through active consulting with welding training experts. Using a minimum viable prototype, we conducted a user study with 24 novices to test the system’s usability. Our findings show (1) greater effectiveness of the system in transferring skills to real-world environments as compared to accessible video-based alternatives and, (2) the visuo-haptic guidance during virtual welding enhances performance and provides a realistic learning experience to users. Using the solution, we expect inexperienced users to achieve competencies faster and be better prepared to enter actual work environments.
Ananya Ipsita, Levi Erickson, Yangzi Dong, Joey Huang, Alexa Bushinski, Sraven Saradhi, Ana M. Villanueva, Kylie Peppler, Thomas Redick, Karthik Ramani
CHI1
2022 ScalAR: Authoring Semantically Adaptive Augmented Reality Experiences in Virtual Reality
abstract
Augmented Reality (AR) experiences tightly associate virtual contents with environmental entities. However, the dissimilarity of different environments limits the adaptive AR content behaviors under large-scale deployment. We propose ScalAR, an integrated workflow enabling designers to author semantically adaptive AR experiences in Virtual Reality (VR). First, potential AR consumers collect local scenes with a semantic understanding technique. ScalAR then synthesizes numerous similar scenes. In VR, a designer authors the AR contents’ semantic associations and validates the design while being immersed in the provided scenes. We adopt a decision-tree-based algorithm to fit the designer’s demonstrations as a semantic adaptation model to deploy the authored AR experience in a physical scene. We further showcase two application scenarios authored by ScalAR and conduct a two-session user study where the quantitative results prove the accuracy of the AR content rendering and the qualitative results show the usability of ScalAR.
Xun Qian, Fengming He, Xiyun Hu, Tianyi Wang 0004, Ananya Ipsita, Karthik Ramani
CHI5
2022 EditAR: A Digital Twin Authoring Environment for Creation of AR/VR and Video Instructions from a Single Demonstration
abstract
Augmented/Virtual reality and video-based media play a vital role in the digital learning revolution to train novices in spatial tasks. However, creating content for these different media requires expertise in several fields. We present EditAR, a unified authoring, and editing environment to create content for AR, VR, and video based on a single demonstration. EditAR captures the user’s interaction within an environment and creates a digital twin, enabling users without programming backgrounds to develop content. We conducted formative interviews with both subject and media experts to design the system. The prototype was developed and reviewed by experts. We also performed a user study comparing traditional video creation with 2D video creation from 3D recordings, via a 3D editor, which uses freehand interaction for in-headset editing. Users took 5 times less time to record instructions and preferred EditAR, along with giving significantly higher usability scores.
Subramanian Chidambaram, Sai Swarup Reddy, Matthew Rumple, Ananya Ipsita, Ana M. Villanueva, Thomas Redick, Wolfgang Stuerzlinger, Karthik Ramani
ISMAR4
2020 StoryMakAR: Bringing Stories to Life With An Augmented Reality & Physical Prototyping Toolkit for Youth
abstract
Makerspaces can support educational experiences in prototyping for children. Storytelling platforms enable high levels of creativity and expression, but have high barriers of entry. We introduce StoryMakAR, which combines making and storytelling. StoryMakAR is a new AR-IoT system for children that uses block programming, physical prototyping, and event-based storytelling to bring stories to life. We reduce the barriers to entry for youth (Age=14-18) by designing an accessible, plug-and-play system through merging both electro-mechanical devices and virtual characters to create stories. We describe our initial design process, the evolution and workflow of StoryMakAR, and results from multiple single-session workshops with 33 high school students. Our preliminary studies led us to understand what students want to make. We provide evidence of how students both engage and have difficulties with maker-based storytelling. We also discuss the potential for StoryMakAR to be used as a learning environment for classrooms and younger students.
Terrell Glenn, Ananya Ipsita, Caleb Carithers, Kylie Peppler, Karthik Ramani
CHI2