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Ryan Jones

dblp:182/7189 · DBLP profile ↗
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2ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0001-7982-8737ORCID · reported

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

Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1Human-computer interaction and ubiquitous computing · 1

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
2 papers
Audio and music processing · 50% Computational photography and imaging · 39% Virtual and augmented reality · 11%
Human-computer interaction and pervasive computing
1 paper
Learning and educational technologies · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Audio and music processing › acoustic signal processing
audio signal reconstruction
0.912025
Event-Based Visual Microphone Based on Specular Reflections Off Angularly Deformed Surfaces · IEEE Trans. Pattern Anal. Mach. Intell. 2025
Computational photography and imaging
event camera
0.912025
Event-Based Visual Microphone Based on Specular Reflections Off Angularly Deformed Surfaces · IEEE Trans. Pattern Anal. Mach. Intell. 2025
Audio and music processing › speech processing
speech reconstruction
0.312025
Event-Based Visual Microphone Based on Specular Reflections Off Angularly Deformed Surfaces · IEEE Trans. Pattern Anal. Mach. Intell. 2025
Virtual and augmented reality › augmented reality
projection-based augmented reality
0.212016
Using projection AR to add design studio pedagogy to a CS classroom · VR 2016
Learning and educational technologies › computing education
computer science education
0.212016
Using projection AR to add design studio pedagogy to a CS classroom · VR 2016
Learning and educational technologies › active learning
peer learning
0.112016
Using projection AR to add design studio pedagogy to a CS classroom · VR 2016

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

specular reflection analysis · 0.9short-time fourier sparsity · 0.9event-based sensing · 0.9
YearPublicationVenuePosition
2025 Event-Based Visual Microphone Based on Specular Reflections Off Angularly Deformed Surfaces
abstract
We propose and demonstrate the event-based visual microphone (EBVM), a passive electro-optical technique for remotely capturing audio signals using an event-based camera without any use of a conventional microphone. The event-based camera records local angular deformations of a surface induced by the sound propagation by observing the changes in the specular reflections at each pixel. By interpreting the timings of the specular incidences deduced from the event stream as signal level-crossings, we reconstruct the audio signal by imposing short-time Fourier sparsity conditions. The recovered audio signal is qualitatively comparable to or better than the prior art (intensity-based visual microphone), while simultaneously expanding the field of view by approximately 25 times and reducing data volume by three orders of magnitude. The proposed EBVM was tested on speech signal reconstruction as well as novel event-based acousto-optical passive ranging.
Ryan Jones, Keigo Hirakawa
IEEE Trans. Pattern Anal. Mach. Intell.2
2016 Using projection AR to add design studio pedagogy to a CS classroom
abstract
The goal of this project is to use projection augmented reality to add design studio learning models to a classroom for an introductory Media Computation computer science class. Students do classwork using an enhanced version of Pythy, a web IDE for Python and Jython, that captures students' work and displays it around the room. We leverage the Microsoft RoomAlive Toolkit to construct a room-scale augmented reality using pairs of projectors and depth cameras. The system “pins” students' work to the walls, where teachers and students can see and discuss the work. We hope that by seeing each other's work, the system will foster collaboration and support the creation of STEM learning experiences that encourage creativity, innovation, and help build strong peer learning environments.
Blair MacIntyre, Dingtian Zhang, Ryan Jones, Amber Solomon, Betsy James DiSalvo, Mark Guzdial
VR3