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Jessica Lai

dblp:318/8055 · DBLP profile ↗
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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

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Human-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.

Human-computer interaction and pervasive computing
1 paper
Haptics and multimodal interaction · 100%
Computer graphics and multimedia
1 paper
Virtual and augmented reality · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Virtual and augmented reality
virtual environment
0.612022
The Smell Engine: A system for artificial odor synthesis in virtual environments · VR 2022
Haptics and multimodal interaction › olfactory interfaces
olfactory display
0.612022
The Smell Engine: A system for artificial odor synthesis in virtual environments · VR 2022
Haptics and multimodal interaction › multimodal interaction
multimodal virtual environment
0.212022
The Smell Engine: A system for artificial odor synthesis in virtual environments · VR 2022

Methods — techniques the papers use, named apart from their topics

user study · 1.1diffusion model · 1.1
YearPublicationVenuePosition
2022 The Smell Engine: A system for artificial odor synthesis in virtual environments
abstract
Mimicking physical odor sensations virtually can present users with a real - time odor synthesis that approximates what users would smell in a virtual environment, e.g., as they walk around in virtual reality. To this end, we devise a Smell Engine that includes: (i) a Smell Composer framework that allows developers to configure odor sources in virtual space, (ii) a Smell Mixer that dynamically estimates the odor mix that the user would smell, based on diffusion models and relative odor source distances, and (iii) a Smell Controller that coordinates an olfactometer to physically present an approximation of the odor mix to the user’s mask from a set of odorants channeled through controllable flow valves. Through a three - part user study, we found that the Smell Engine can help measure a subject’s olfactory detection threshold and improve their ability to precisely localize odors in the virtual environment, as compared to existing trigger - based solutions.
Alireza Bahremand, Mason Manetta, Jessica Lai, Byron Lahey, Christy Spackman, Brian H. Smith, Richard C. Gerkin, Robert LiKamWa
VR3