Demo Data from VLDB 2026 / reviewers in the wild / expert
Pashin Farsak Raja
dblp:332/0566
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Virtual and augmented reality · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Personal fabrication and tangible interfaces · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Virtual and augmented reality › augmented reality
augmented reality authoring |
0.6 | 1 | 2022 | MechARspace: An Authoring System Enabling Bidirectional Binding of Augmented Reality with Toys in Real-time · UIST 2022 |
Methods — techniques the papers use, named apart from their topics
visual programming · 1.1elicitation study · 1.1direct manipulation · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | MechARspace: An Authoring System Enabling Bidirectional Binding of Augmented Reality with Toys in Real-timeabstractAugmented Reality (AR), which blends physical and virtual worlds, presents the possibility of enhancing traditional toy design. By leveraging bidirectional virtual-physical interactions between humans and the designed artifact, such AR-enhanced toys can provide more playful and interactive experiences for traditional toys. However, designers are constrained by the complexity and technical difficulties of the current AR content creation processes. We propose MechARspace, an immersive authoring system that supports users to create toy-AR interactions through direct manipulation and visual programming. Based on the elicitation study, we propose a bidirectional interaction model which maps both ways: from the toy inputs to reactions of AR content, and also from the AR content to the toy reactions. This model guides the design of our system which includes a plug-and-play hardware toolkit and an in-situ authoring interface. We present multiple use cases enabled by MechARspace to validate this interaction model. Finally, we evaluate our system with a two-session user study where users first recreated a set of predefined toy-AR interactions and then implemented their own AR-enhanced toy designs. Zhengzhe Zhu, Ziyi Liu 0004, Tianyi Wang 0004, Youyou Zhang, Xun Qian, Pashin Farsak Raja, Ana M. Villanueva, Karthik Ramani |
UIST | 6 |