Related papers: Light-weight Gesture Sensing Using FMCW Radar Time…
At present, applications of biometrics are rapidly increasing due to inconveniences in using traditional passwords and physical keys. Hand geometry, one of the most well-known biometrics, is implemented in many verification systems with…
The millimeter-wave (mmWave) radar has been exploited for gesture recognition. However, existing mmWave-based gesture recognition methods cannot identify different users, which is important for ubiquitous gesture interaction in many…
Hand gestures can provide a natural means of human-computer interaction and enable people who cannot speak to communicate efficiently. Existing hand gesture recognition methods heavily depend on pre-defined gestures, however, motor-impaired…
We are concerned with a novel sensor-based gesture input/instruction technology which enables human beings to interact with computers conveniently. The human being wears an emitter on the finger or holds a digital pen that generates a time…
Robotic manipulation systems operating in complex environments rely on perception systems that provide information about the geometry (pose and 3D shape) of the objects in the scene along with other semantic information such as object…
In this paper, we extend our method [1] for FMCW radar mutual interference mitigation (IM) based on the discrete fractional Fourier transform (DFrFT). Firstly, we propose a radar signal processing chain including our DFrFT-based IM for…
While machine learning is widely used to optimize wireless networks, training a separate model for each task in communication and localization is becoming increasingly unsustainable due to the significant costs associated with training and…
Online recognition of gestures is critical for intuitive human-robot interaction (HRI) and further push collaborative robotics into the market, making robots accessible to more people. The problem is that it is difficult to achieve accurate…
The method of deep learning has achieved excellent results in improving the performance of robotic grasping detection. However, the deep learning methods used in general object detection are not suitable for robotic grasping detection.…
In the field of gestural action recognition, many studies have focused on dimensionality reduction along the spatial axis, to reduce both the variability of gestural sequences expressed in the reduced space, and the computational complexity…
In this paper, a novel proactive computing and mmWave communication for ultra-reliable and low latency wireless virtual reality (VR is proposed. By leveraging information about users' poses, proactive computing and caching are used to…
Recent trend of touch-screen devices produces an accessibility barrier for visually impaired people. On the other hand, these devices come with sensors such as accelerometer. This calls for new approaches to human computer interface (HCI).…
Internet of Things is rapidly spreading across several fields, including healthcare, posing relevant questions related to communication capabilities, energy efficiency and sensors unobtrusiveness. Particularly, in the context of recognition…
We propose a novel appearance-based gesture recognition algorithm using compressed domain signal processing techniques. Gesture features are extracted directly from the compressed measurements, which are the block averages and the coded…
This paper presents a novel micro-Doppler energy-based framework for robust multi-target vital signs monitoring using 77-GHz Frequency-Modulated Continuous-Wave (FMCW) radar. Unlike conventional phase-based methods that are susceptible to…
Wi-Fi gesture recognition based on Channel State Information (CSI) is challenged by high-dimensional noise and resource constraints on edge devices. Prevailing end-to-end models tightly couple feature extraction with classification,…
Hand gesture recognition (HGR) is a fundamental technology in human computer interaction (HCI).In particular, HGR based on Doppler radar signals is suited for in-vehicle interfaces and robotic systems, necessitating lightweight and…
Radar-based human activity recognition has gained attention as a privacy-preserving alternative to vision and wearable sensors, especially in sensitive environments like long-term care facilities. Micro-Doppler spectrograms derived from…
Automatic surgical gesture recognition is a prerequisite of intra-operative computer assistance and objective surgical skill assessment. Prior works either require additional sensors to collect kinematics data or have limitations on…
We design a gesture-recognition pipeline for networks of distributed, resource constrained devices utilising Einsum Networks. Einsum Networks are probabilistic circuits that feature a tractable inference, explainability, and energy…