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Zhehui Yin

dblp:408/0797 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
—ORCID · conflict

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

Computer networks · 2 · 2 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
2 papers
Wireless sensing and localization · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wireless sensing and localization
mmwave sensing
1.012026
MuPose: Breaking the Scalability Barrier of mmWave Multi-User Pose Estimation in the Wild · MobiSys 2026
Wireless sensing and localization › radar sensing
mmwave radar sensing
0.912025
mmRotation: Unlocking Versatility of a Single mmWave Radar via Azimuth Panning and Elevation Tilting · IEEE Trans. Mob. Comput. 2025
Wireless sensing and localization › human activity recognition
fall detection
0.312025
mmRotation: Unlocking Versatility of a Single mmWave Radar via Azimuth Panning and Elevation Tilting · IEEE Trans. Mob. Comput. 2025
Wireless sensing and localization
vital sign monitoring
0.312025
mmRotation: Unlocking Versatility of a Single mmWave Radar via Azimuth Panning and Elevation Tilting · IEEE Trans. Mob. Comput. 2025

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

radar orientation adjustment · 0.9automated calibration · 0.9
YearPublicationVenuePosition
2026 MuPose: Breaking the Scalability Barrier of mmWave Multi-User Pose Estimation in the Wild
Zhehui Yin, Hongliu Yang, Zhiyun Yao, Zizhou Fan, Daqing Zhang 0001
MobiSys2
2025 mmRotation: Unlocking Versatility of a Single mmWave Radar via Azimuth Panning and Elevation Tilting
abstract
Indoor mmWave-based sensing technologies have garnered substantial interest from both the industrial and academic. Yet, the intrinsic challenge posed by the limited Field-of-View (FOV) of mmWave radars significantly restricts their coverage. This limitation necessitates careful selection of installation positions and orientations to optimize performance, thereby severely curtailing the versatility and widespread adoption of these systems. Traditionally, expanding coverage involved increasing the number of radar units. This paper introduces a novel approach to enhance the FOV by incorporating mobility, achieved by affixing the radar onto a pan-tilt unit capable of rotating along both the horizontal and azimuthal. Nevertheless, the disparity between the pan-tilt and the radar presents significant challenges for accurately rotating the radar's orientation. To mitigate this, we propose an automated calibration algorithm for radar and pan-tilt, ensuring precise calibration. Additionally, we have devised a radar orientation adjustment algorithm intended to automatically align the radar's FOV with the positions of detected objects to facilitate various applications. Through three case studies, we have demonstrated that mmRotation can greatly expand the sensing range, enabling support for multiple applications on a single radar, such as vital signs monitoring and fall detection. Comprehensive experimental results underscore that our system surpasses the current state-of-the-art (SOTA).
Zhehui Yin, Yaxiong Xie, Hewen Wei, Zhaoxin Chang 0001, Daqing Zhang 0001
IEEE Trans. Mob. Comput.3