1,721,029 research outputs found
RF-Pointer: a novel approach to radio-frequency driven pointer technology for HCI
No full textThis paper introduces the 'RF-Pointer,' an innovative radio-frequency-based interaction framework designed for real-time tracking and projection of hand movements in virtual spaces. The system can provide a hands-free and distinctive interaction experience suitable for emerging domains like virtual reality and augmented reality. In this study, we delve into the architectural and operational dynamics of the RF-Pointer, utilizing a prototype equipped with a 77 GHz radar sensor. Initial tests reveal an average tracking error of 2.5 cm in estimating the pointer's location. To further illustrate the efficacy of the proposed architecture, we conduct a qualitative comparison, presenting the results in the form of tracked trajectories corresponding to both ground truth and the RF-Pointer estimated trajectories. The tracking results demonstrate that RF-Pointer trajectories closely align with ground truth trajectories.</p
Reducing the Computational Complexity of WiFi-Based Passive Radar Processing
Full text linkWiFi-based passive radar is considered in this paper as an effective technology for short range monitoring applications. Aiming at limiting its complexity and enhancing its suitability for civilian applications, appropriate modifications are proposed to the signal processing scheme originally designed for such sensor. Specifically, we show that a simple inversion in the order of the main processing stages, namely clutter cancellation and range compression, allows to both reduce the number of floating-point operations and relax the requirements on the data management. Moreover, the use of a reciprocal filter in lieu of a matched filter to implement the range compression stage is proved to yield a further simplification in the resulting processing scheme along with additional benefits in terms of achievable performance in the considered application. The alternative processing schemes are compared in terms of computational burden and the effectiveness of the proposed cost-effective solutions is proved against experimental datasets
Using RF transmissions from IoT devices for occupancy detection and activity recognition
No full textIoT ecosystems consist of a range of smart devices that generated a plethora of Radio Frequency (RF) transmissions. This provides an attractive opportunity to exploit already-existing signals for various sensing applications such as e-Healthcare, security and smart home. In this paper, we present Passive IoT Radar (PIoTR), a system that passively uses RF transmissions from IoT devices for human monitoring. PIoTR is designed based on passive radar technology, with a generic architecture to utilize various signal sources including the WiFi signal and wireless energy at the Industrial, Scientific and Medical (ISM) band. PIoTR calculates the phase shifts caused by human motions and generates Doppler spectrogram as the representative. To verify the proposed concepts and test in a more realistic environment, we evaluate PIoTR with four commercial IoT devices for home use. Depending on the effective signal and power strength, PIoTR performs two modes: coarse sensing and fine-grained sensing. Experimental results show that PIoTR can achieve an average of 91% in occupancy detection (coarse sensing) and 91.3% in activity recognition (fine-grained sensing)
Reference-Free Passive RF Imaging Using Near-Field Spatial Processing
No full textPassive radar imaging has been extensively studied and is based on an illuminator-of-opportunity, such as a wireless access point, providing a signal that scatters from targets and is incident on a receiving node(s) in order to infer information on the range and velocity of the target scene. Such systems universally require reference signal regeneration, from a dedicated channel, that is cross-correlated with the received signal in order to extract the range/Doppler information of the target. This paper presents one of several techniques developed by the authors to achieve passive radar (or RF) imaging without any requirement for extraction of the reference signal. The concept is analogous to optical systems in which various source(s) provide general illumination of a target scene, the scattered signals of which are gathered and processed at an optical sensor in order to reconstruct the image, but without any requirement to extract the illumination (reference) source itself. Such an approach offers numerous practical advantages in achieving imaging from a single passive sensor without the additional requirement of precise, or indeed any, regeneration of the illuminating source: a reference-free approach. This paper presents one such technique based on sampling of the complex signal distribution over an antenna aperture and near-field processing to form a two/three-dimensional reconstruction of the target scene. The fundamental principles of the technique are described along with analysis of basic performance limits. Modelling is presented to illustrate the capability of the technique, which is validated by experimental measurement with a WiFi access point-based prototype system
MDPose: human skeletal motion reconstruction using WiFi micro-doppler signatures
No full textMotion tracking systems based on optical sensors typically suffer from poor lighting conditions, occlusion, limited coverage, and may raise privacy concerns. More recently, radiofrequency (RF) based approaches using commercial WiFi devices have emerged which offer low-cost ubiquitous sensing whilst preservin privacy. However, RF sensing systems typically output range-Doppler maps, time-frequency spectrograms, cross-range plots etc which cannot represent human motion intuitively and usually requires further processing. In this study, we propose MDPose, a novel framework for human skeletal motion reconstruction base on WiFi micro-Doppler signatures. MDPose provides an effective solution to represent human activity by reconstructing a skeleton model with 17 key points, which can assist with the interpretation of conventional RF sensing outputs in a more understandable way. Specifically, MDPose is implemented over three sequential stage to address a series of challenges: First, a denoising algorithm is employed to remove any unwanted noise that may affect feature extraction and enhance weak Doppler measurements. Secondly, a convolutional neural network (CNN)-recurrent neural network (RNN) architecture is applied to learn temporal spatial dependenc from clean micro-Doppler signatures and restore velocity information to key points under the supervision of the motion capture (Mocap) system. Finally, a pose optimisation mechanism based on learning optimisation vectors is employed to estimate the initial state of the skeleton and to limit additional errors. We hav conducted a comprehensive set of tests in a variety of environments using numerous subjects with a single receiver radar system to demonstrate the performance of MDPose, and report 29.4mm mean absolute error over all key points positions on several common daily activities, which has performance comparable to that of state-ofthe- art RF-based pose estimation systems
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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