1. Current state and future research directions of radar-based human-computer interactionKlen Čopič Pucihar, Dariush Salami, Nuwan Attygalle, 2026, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: This chapter provides an overview of the current state of radar-based Human-Computer Interaction (HCI) and outlines future research directions. While earlier chapters in this book have explored specialised domains, such as through-material sensing, ambient intelligence, surface context awareness, hand air-writing, and on-object gesture detection, this chapter expands this perspective by examining fifty carefully selected publications that address a broad range of design and technical considerations in radar-based HCI. We review key design choices, including gesture set definitions, sensor placements, radar types, frequency ranges, signal representations, and classification algorithms. Building on this foundation, the chapter then presents a forward-looking discussion of research opportunities. Particular emphasis is placed on the need for miniaturised, energy-efficient, and adaptive radar systems capable of functioning reliably in diverse, real-world settings. Additionally, the chapter stresses the importance of developing open, standardised datasets to support reproducibility, improve generalizability, and promote inclusive design.
Ključne besede: radar-based human-computer interaction, future directions, current state
Objavljeno v RUP: 19.05.2026; Ogledov: 217; Prenosov: 10
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2. Radar-based gesture recognition on deformable objectsKlen Čopič Pucihar, Matjaž Kljun, Nuwan Attygalle, 2026, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: This chapter investigates the feasibility and challenges of using millimetre-wave radar for gesture recognition on deformable objects, such as plush toys or other objects made of flexible materials, which are typically not instrumented with sensors. Unlike vision-based systems, which are limited by occlusion and require clear line of sight, radar sensing can detect gestures through non-conductive materials. The authors compare prior work on gesture recognition performance across mid-air, on-object and on-deformable-object contexts using different radar signal representations and deep learning models. In addition, the authors conduct an experiment demonstrating that object deformations do not negatively impact recognition accuracy. These findings open new possibilities for contactless interaction with soft materials in everyday environments without requiring embedded instrumentation.
Ključne besede: radar, gesture recognition, deformable objects
Objavljeno v RUP: 18.05.2026; Ogledov: 236; Prenosov: 10
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3. Radar-based human-computer interaction when sensing through materialsNuwan Attygalle, Matjaž Kljun, Arthur Sluÿters, Klen Čopič Pucihar, 2026, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: We increasingly interact with computing devices that are either worn on the body (e.g. smartphones, smartwatches) or are embedded within our surroundings (e.g. smart homes, smart offices). These interactions occur through a variety of input methods, including physical buttons and knobs, mid-air gestures, touch and voice commands. With the exception of voice, these modalities require direct or near-direct physical contact with the device, typically involving line-of-sight or proximity for touch or grasp. However, interaction becomes constrained or entirely infeasible (i) when the interaction device is covered (e.g. when a smartphone is inside a pocket or a smartwatch is covered by a jacket sleeve), (ii) in sterile environments requiring separation between the user and device (e.g. when wearing personal protective equipment) or (iii) when interfaces are deliberately concealed for aesthetic, safety or functional reasons. Enabling interaction in such contexts is important to leverage the computational capabilities embedded in our environments. Yet, current technologies remain limited when interaction through occluding materials is needed. In this chapter, we examine existing research on the use of radar-based systems for interaction through materials, focusing on how materials affect system performance, principles for designing such interfaces and strategies to advance these systems.
Ključne besede: radar, human-computer interaction, sensing through materials
Objavljeno v RUP: 18.05.2026; Ogledov: 239; Prenosov: 9
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4. Comparative testing of radar signal representations when sensing through materialsNuwan Attygalle, Matjaž Kljun, Una Vuletić, Klen Čopič Pucihar, 2026, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: The ability to sense mid-air gestures with miniaturised radars embedded in everyday objects opens up new opportunities for interaction. Applications include integration into wearable devices, automotive dashboards, smart furniture, and other components within smart environments. Despite this potential, the lack of studies on how various occluding materials affect gesture recognition performance hinders progress in this area. Previous studies have primarily focused on evaluating only one type of radar signal representation, despite the fact that several other representations exist and were proved effective. To address this, the chapter presents a comparative evaluation of four radar signal representations: In-phase and Quadrature (IQ) representations in the frequency domain and magnitude and range-angle (including both elevation and azimuth components) and range-Doppler. The goal is to assess their robustness against signal distortions introduced by occluding materials. Preliminary results indicate that recognition performance tends to improve with a higher transmission coefficient. Moreover, range-Doppler and range-angle representations exhibit significantly greater robustness to distortion compared to IQ representations
Ključne besede: comparative testing, radar signal representations, sensing through materials
Objavljeno v RUP: 18.05.2026; Ogledov: 223; Prenosov: 10
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5. Digital signal processing tools for radar-based human-computer interactionNuwan Attygalle, Matjaž Kljun, Klen Čopič Pucihar, 2026, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: In recent years, miniature radar-on-chip sensors have been explored for HCI by both academia and industry. This is driven by the availability of affordable radar hardware and advances in signal processing and machine learning. However, comparative evaluation of radar-based gesture interaction systems is challanging and rear. One important dimension for comparison is the set of radar signal representa- tions derived from raw voltage data. These representations commonly include range- Doppler, range-azimuth-angle, range-elevation-angle, point cloud and In-phase and Quadrature (IQ) radar cube formats. However, existing studies often restrict com- parative analysis to a single signal representation type, typically focusing on gesture recognition algorithms or minor variations within Digital Signal Processing (DSP) pipelines. To promote comparative evaluation of radar signal representations, this chapter develops an open-source application designed to facilitate efficient and reli- able dataset preparation of various radar signal representations. The application sup- ports visualisation of generated signal representations and includes a command-line interface for batch processing, thereby streamlining the dataset preparation workflow.
Ključne besede: digital signal processing, radar, human-computer interaction
Objavljeno v RUP: 18.05.2026; Ogledov: 260; Prenosov: 7
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6. Gesture recognition on deformable objects using millimeter-wave radarNuwan Attygalle, Matjaž Kljun, Klen Čopič Pucihar, 2025, objavljeni znanstveni prispevek na konferenci Opis: 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.
Ključne besede: gesture recognition, deformable objects, millimeter-wave radar
Objavljeno v RUP: 23.06.2025; Ogledov: 1121; Prenosov: 11
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7. No interface, no problem : gesture recognition on physical objects using radar sensingNuwan Attygalle, Luis A. Leiva, Matjaž Kljun, Christian Sandor, Alexander Plopski, Hirokazu Kato, Klen Čopič Pucihar, 2021, izvirni znanstveni članek Ključne besede: radar sensing, gesture recognition, deep learning
Objavljeno v RUP: 18.10.2021; Ogledov: 3539; Prenosov: 26
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8. The wearable radar : sensing gestures through fabricsLuis A. Leiva, Matjaž Kljun, Christian Sandor, Klen Čopič Pucihar, 2020, objavljeni znanstveni prispevek na konferenci Ključne besede: radar, wearables, fabrics, Soli, gestures, deep learning
Objavljeno v RUP: 06.05.2021; Ogledov: 3635; Prenosov: 36
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9. The missing interface : micro-gestures on augmented objectsKlen Čopič Pucihar, Christian Sandor, Matjaž Kljun, Wolfgang Huerst, Alexander Plopski, Takafumi Taketomi, Hirokazu Kato, Luis A. Leiva, 2019, objavljeni znanstveni prispevek na konferenci Ključne besede: augmented reality, Google Soli, millimeter-wave radar, micro-gesture recognition
Objavljeno v RUP: 22.05.2019; Ogledov: 4100; Prenosov: 126
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10. In situ assessment of structural timber using non-destructive techniquesMariapaola Riggio, Ronald W. Anthony, Francesco Augelli, Bohumil Kasal, Thomas Lechner, Wayne Muller, T. Tannert, 2014, izvirni znanstveni članek Ključne besede: visual inspection, moisture content determination, species identification, digital radioscopy, ground penetrating radar
Objavljeno v RUP: 19.11.2018; Ogledov: 4497; Prenosov: 238
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