Demo Data from EDBT 2026 / reviewers in the wild / expert
Freddy Yifei Liu
dblp:420/3204
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0004-9992-7339ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 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% | |
| Human-computer interaction and pervasive computing
1 paper |
Wearable and physiological sensing · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wireless sensing and localization › device-free sensing
device-free localization |
1.0 | 1 | 2026 | Motion Capture with Millimeter-Wave Tags · SenSys 2026 |
Wireless sensing and localization
mmwave sensing |
1.0 | 1 | 2026 | Motion Capture with Millimeter-Wave Tags · SenSys 2026 |
Wireless sensing and localization › human sensing › human activity sensing
motion capture |
1.0 | 1 | 2026 | Motion Capture with Millimeter-Wave Tags · SenSys 2026 |
Wearable and physiological sensing › motion sensing
motion tracking |
0.3 | 1 | 2026 | Motion Capture with Millimeter-Wave Tags · SenSys 2026 |
Methods — techniques the papers use, named apart from their topics
phase-based tracking · 2.0backscatter communication · 2.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Motion Capture with Millimeter-Wave TagsabstractThis paper introduces M3oCap, a millimeter-wave (mmWave) tag-based motion capture system that delivers accurate 6 degrees of freedom motion tracking. M3oCap utilizes a single commercial mmWave radar and custom-designed mmWave backscatter tags (2.5 cm × 3 cm) to localize and track the motion of tagged objects. Our system features novel algorithms that effectively isolate weak backscattered signals while accurately recovering phase changes induced by motion, allowing high-rate tracking of tag movements. Experiments show that M3oCap achieves performance close to commercial motion capture systems – it provides 1000 measurements per second with a median range tracking accuracy of 250 μ m, median localization accuracies of 3.34 mm, 3.95 mm, and 4.20 mm in x, y, z dimensions, and median orientation tracking accuracies of 1.7°, 2.3°, and 2.0° across pitch, roll, and yaw. We further demonstrate the system’s fine-grained movement tracking capabilities through various motion capture tasks. Freddy Yifei Liu, Yunshuang Li, Yao Gong, Dinesh Jayaraman, Omid Abari, Mingmin Zhao |
SenSys | 2 |