20.500.12556/RUP-21375 Gesture recognition on deformable objects using millimeter-wave radar Although deformable objects are not typically designed for digital interaction, they offer a largely unexplored potential—any such object could be repurposed as a medium for controlling digital content. While existing approaches embed sensors into deformable objects to enable interaction, this limits scalability and practicality of such systems. An alternative is to perform gesture recognition on deformable objects using a wrist-worn radar sensor. However, when analysing reflected radar signals it is difficult to separate reflections originating from the continues deformations of the object shape and those from the user’s hand and fingers. Additionally, the continuous shape changes of deformable objects introduce changes in radar cross-section, affecting signal variability. Furthermore, user ergonomics—such as variations in hand size, finger dexterity, and strength—are likely to influence the degree of object deformation during interaction. In this paper, we explore whether radar sensing can be used for robust gesture detection on deformable objects, focusing on how well does a system generalize to previously unseen users and what can we do to improve such generalisability. In pursuit of this goal, we record a dataset of 4.3k labelled gestures with Google Soli millimeter-wave radar sensor on a plush toy and demonstrates robust classification performance, achieving accuracy of up to 90% on a five-gesture set. Furthermore, we investigate model generalizability and show that transfer learning improves recognition for previously unseen users, yielding performance gains of up to 20%. These findings highlight the potential of radar-based sensing for spontaneous and practical interaction with deformable objects. gesture recognition deformable objects millimeter-wave radar prepoznavanje gest deformabilni predmeti radar z milimetrskim valovanjem true false false Angleški jezik Slovenski jezik Neznano 2025-06-23 15:11:14 2025-06-23 15:11:16 2025-06-28 03:03:31 0000-00-00 00:00:00 2025 0 0 Str. 50-58 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 2025-06-22 004.9 240288003 10.1145/3731406.3734979 240291331 https://dl.acm.org/doi/10.1145/3731406.3734979 1 775b8b4f-5033-11f0-bc14-005056ac49c0 https://repozitorij.upr.si/Dokument.php?lang=slv&id=31089 RAZ_Attygalle_Nuwan_2025.pdf RAZ_Attygalle_Nuwan_2025.pdf 1 0F8D6BEFC63FC86683974C9764BD72EE 0362b314ebeb1c5028ca48ed436448948d52f300ba43fa53c75147e14b0dcd60 a27b6152-5331-11f0-bc14-005056ac49c0 https://repozitorij.upr.si/Dokument.php?lang=slv&id=31105 Fakulteta za matematiko, naravoslovje in informacijske tehnologije 0 0 0