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Ruiming Huang

dblp:377/0720 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2025
0000-0002-0807-1036ORCID · corroborated

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

Computer networks · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 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 networks
1 paper
Wireless sensing and localization · 100%
Computer graphics and multimedia
1 paper
Multimedia analysis and retrieval · 100%
Human-computer interaction and pervasive computing
1 paper
Health and well-being technologies · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Multimedia analysis and retrieval
audio-visual learning
0.912025
CardioLive: Empowering Video Streaming with Online Cardiac Monitoring via Audio-Visual Learning · ACM Multimedia 2025
Health and well-being technologies › health monitoring
cardiac monitoring
0.912025
CardioLive: Empowering Video Streaming with Online Cardiac Monitoring via Audio-Visual Learning · ACM Multimedia 2025
Wireless sensing and localization
acoustic sensing
0.812024
Demo: Statistical Acoustic Sensing For Real-Time Respiration Monitoring and Presence Detection · MobiSys 2024
Wireless sensing and localization › vital sign monitoring
respiration monitoring
0.812024
Demo: Statistical Acoustic Sensing For Real-Time Respiration Monitoring and Presence Detection · MobiSys 2024

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

audio-visual learning · 1.7channel frequency response · 0.8autocorrelation function · 0.8
YearPublicationVenuePosition
2025 CardioLive: Empowering Video Streaming with Online Cardiac Monitoring via Audio-Visual Learning
Sheng Lyu, Ruiming Huang, Sijie Ji, Yasar Abbas Ur Rehman, Chenshu Wu
ACM Multimedia2
2024 Demo: Statistical Acoustic Sensing For Real-Time Respiration Monitoring and Presence Detection
abstract
In this demo, we present an all-in-one real-time system for breathing monitoring and presence detection using statistical acoustic sensing. By applying Auto-Correlation Function (ACF) to the Channel Frequency Response (CFR), our system captures both motion statistics and breathing rates. We devise novel weight combining schemes to enhance the SNR of the weak sensing signals. We then enable human presence detection by integrating both motion statistics and breathing rate as vital indicators. Our system operates using a single microphone without relying on a bulky microphone array. Our demo functions in real-time and supports any device that is equipped with a commodity microphone and speaker. Our demo can be accessed through https://youtu.be/JUB6yQ1rQUo
Sheng Lyu, Ruiming Huang, Yuemin Yu, Chenshu Wu
MobiSys2