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DTSTAMP:20240214T070248Z
LOCATION:Meeting Room C4.8\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231214T151500
DTEND;TZID=Australia/Melbourne:20231214T152500
UID:siggraphasia_SIGGRAPH Asia 2023_sess158_papers_588@linklings.com
SUMMARY:Hand Pose Estimation with Mems-Ultrasonic Sensors
DESCRIPTION:Technical Papers\n\nQiang Zhang, Yuanqiao Lin, Yubin Lin, and 
 Szymon Rusinkiewicz (Princeton University)\n\nHand tracking is an importan
 t aspect of human-computer interaction and has a wide range of application
 s in extended reality devices. However, current hand motion capture method
 s suffer from various limitations. For instance, visual-based hand pose es
 timation is susceptible to self-occlusion and changes in lighting conditio
 ns, while IMU-based tracking gloves experience significant drift and are n
 ot resistant to external magnetic field interference. To address these iss
 ues, we propose a novel and low-cost hand-tracking glove that utilizes sev
 eral MEMS-ultrasonic sensors attached to the fingers, to measure the dista
 nce matrix among the sensors. Our lightweight deep network then reconstruc
 ts the hand pose from the distance matrix. Our experimental results demons
 trate that this approach is both accurate, size-agnostic, and robust to ex
 ternal interference. We also show the design logic for the sensor selectio
 n, sensor configurations, circuit diagram, as well as model architecture.\
 n\nRegistration Category: Full Access\n\nSession Chair: Jae-Ho Nah (Sangmy
 ung University)
URL:https://asia.siggraph.org/2023/full-program?id=papers_588&sess=sess158
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