scholarly journals Multimodal Hand Gesture Classification for the Human–Car Interaction

Informatics ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 31
Author(s):  
Andrea D’Eusanio ◽  
Alessandro Simoni ◽  
Stefano Pini ◽  
Guido Borghi ◽  
Roberto Vezzani ◽  
...  

The recent spread of low-cost and high-quality RGB-D and infrared sensors has supported the development of Natural User Interfaces (NUIs) in which the interaction is carried without the use of physical devices such as keyboards and mouse. In this paper, we propose a NUI based on dynamic hand gestures, acquired with RGB, depth and infrared sensors. The system is developed for the challenging automotive context, aiming at reducing the driver’s distraction during the driving activity. Specifically, the proposed framework is based on a multimodal combination of Convolutional Neural Networks whose input is represented by depth and infrared images, achieving a good level of light invariance, a key element in vision-based in-car systems. We test our system on a recent multimodal dataset collected in a realistic automotive setting, placing the sensors in an innovative point of view, i.e., in the tunnel console looking upwards. The dataset consists of a great amount of labelled frames containing 12 dynamic gestures performed by multiple subjects, making it suitable for deep learning-based approaches. In addition, we test the system on a different well-known public dataset, created for the interaction between the driver and the car. Experimental results on both datasets reveal the efficacy and the real-time performance of the proposed method.

The tool identified for data collection of this research project is a video game, which makes the topic of the representation of space in videogame an absolutely relevant aspect for the project. This work bases on the statement of Jenkins, according to which “game space never exists in abstract, but always experientially”. In the current generation of video games, talking about position of the camera assumes a different value than in film or television language, assuming the meaning of point of view from which the game is visually (and auditory) presented and determines the spatial perspective of a computer game. The most common distinction, with respect to the position of the camera, is between First Person Camera, where space is presented from the perceptive perspective of the player's avatar and Third Person Camera, where the perspective is not directly the one of the avatar. This category, in fact, is very extensive, and poorly lends itself to a single definition. Under the umbrella of Third Person Camera are both perspectives associated with the avatar, but framing it externally (a camera follows the avatar) and those in which the camera is fixed. Moreover, the position of the camera compared to the avatar (from behind, left, right, Orbit Camera, etc.), or with respect to the environment (from above, from a precise point of reference) is not a neutral choice. In the present work, we use the categorization proposed by Britta Neitzel (Neitzel, 2002), which, taking up the work of Jean Mitry about The Aesthetics and Psychology of the Cinema (Mitry & King, 1997), distinguishes between subjective, semisubjective or objectives views. The chapter provides examples of different perspectives, and introduces the concept of Natural User Interfaces, which include movements based on input and output, on discretion, on voice, and evolve towards an efficient use of the senses in the interaction with machines.


2021 ◽  
Vol 13 (14) ◽  
pp. 7578
Author(s):  
Cristian Gómez-Portes ◽  
David Vallejo ◽  
Ana-Isabel Corregidor-Sánchez ◽  
Marta Rodríguez-Hernández ◽  
José L. Martín-Conty ◽  
...  

In recent years, there has been a significant growth in the number of research works focused on improving the lifestyle and health of elderly people by means of technology. Telerehabilitation and the promotion of physical activity at home have been two of the fields that have attracted more attention, especially currently due to the COVID-19 pandemic. However, elderly people are sometimes reluctant to use technology at home, mainly due to fear of technology and lack of familiarity. In this context, this article presents a low-cost platform that relies on exergames and natural user interfaces to promote physical activity at home and improve the quality of life in elderly people. The underlying system is easy to use and accessible, offering a number of interaction mechanisms that guide users through the execution of routines and exercises. A relevant feature of the proposal is the ability to customize the exergames, making it possible for the therapist to adapt them according to the user’s needs. Motivation is also addressed within the developed platform to maintain the user’s engagement level as time passes by. An empirical experiment is conducted to measure the usability and motivational aspects of the proposal, which was evaluated by 17 users between 62 and 89 years of age. The obtained results showed that the proposal was well received, considering that most of the users were not experienced at all with exergame-based systems.


Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 91
Author(s):  
Santiago Lopez-Restrepo ◽  
Andres Yarce ◽  
Nicolás Pinel ◽  
O.L. Quintero ◽  
Arjo Segers ◽  
...  

The use of low air quality networks has been increasing in recent years to study urban pollution dynamics. Here we show the evaluation of the operational Aburrá Valley’s low-cost network against the official monitoring network. The results show that the PM2.5 low-cost measurements are very close to those observed by the official network. Additionally, the low-cost allows a higher spatial representation of the concentrations across the valley. We integrate low-cost observations with the chemical transport model Long Term Ozone Simulation-European Operational Smog (LOTOS-EUROS) using data assimilation. Two different configurations of the low-cost network were assimilated: using the whole low-cost network (255 sensors), and a high-quality selection using just the sensors with a correlation factor greater than 0.8 with respect to the official network (115 sensors). The official stations were also assimilated to compare the more dense low-cost network’s impact on the model performance. Both simulations assimilating the low-cost model outperform the model without assimilation and assimilating the official network. The capability to issue warnings for pollution events is also improved by assimilating the low-cost network with respect to the other simulations. Finally, the simulation using the high-quality configuration has lower error values than using the complete low-cost network, showing that it is essential to consider the quality and location and not just the total number of sensors. Our results suggest that with the current advance in low-cost sensors, it is possible to improve model performance with low-cost network data assimilation.


Author(s):  
Cristina Tassorelli ◽  
Vincenzo Silani ◽  
Alessandro Padovani ◽  
Paolo Barone ◽  
Paolo Calabresi ◽  
...  

Abstract Background The coronavirus disease 2019 (COVID-19) pandemic has severely impacted the Italian healthcare system, underscoring a dramatic shortage of specialized doctors in many disciplines. The situation affected the activity of the residents in neurology, who were also offered the possibility of being formally hired before their training completion. Aims (1) To showcase examples of clinical and research activity of residents in neurology during the COVID-19 pandemic in Italy and (2) to illustrate the point of view of Italian residents in neurology about the possibility of being hired before the completion of their residency program. Results Real-life reports from several areas in Lombardia—one of the Italian regions more affected by COVID-19—show that residents in neurology gave an outstanding demonstration of generosity, collaboration, reliability, and adaptation to the changing environment, while continuing their clinical training and research activities. A very small minority of the residents participated in the dedicated selections for being hired before completion of their training program. The large majority of them prioritized their training over the option of earlier employment. Conclusions Italian residents in neurology generously contributed to the healthcare management of the COVID-19 pandemic in many ways, while remaining determined to pursue their training. Neurology is a rapidly evolving clinical field due to continuous diagnostic and therapeutic progress. Stakeholders need to listen to the strong message conveyed by our residents in neurology and endeavor to provide them with the most adequate training, to ensure high quality of care and excellence in research in the future.


2021 ◽  
Vol 1 ◽  
pp. 283-292
Author(s):  
Jakob Harlan ◽  
Benjamin Schleich ◽  
Sandro Wartzack

AbstractThe increased availability of affordable virtual reality hardware in the last years boosted research and development of such systems for many fields of application. While extended reality systems are well established for visualization of product data, immersive authoring tools that can create and modify that data are yet to see widespread productive use. Making use of building blocks, we see the possibility that such tools allow quick expression of spatial concepts, even for non-expert users. Optical hand-tracking technology allows the implementation of this immersive modeling using natural user interfaces. Here the users manipulated the virtual objects with their bare hands. In this work, we present a systematic collection of natural interactions suited for immersive building-block-based modeling systems. The interactions are conceptually described and categorized by the task they fulfil.


Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2944
Author(s):  
Benjamin James Ralph ◽  
Marcel Sorger ◽  
Benjamin Schödinger ◽  
Hans-Jörg Schmölzer ◽  
Karin Hartl ◽  
...  

Smart factories are an integral element of the manufacturing infrastructure in the context of the fourth industrial revolution. Nevertheless, there is frequently a deficiency of adequate training facilities for future engineering experts in the academic environment. For this reason, this paper describes the development and implementation of two different layer architectures for the metal processing environment. The first architecture is based on low-cost but resilient devices, allowing interested parties to work with mostly open-source interfaces and standard back-end programming environments. Additionally, one proprietary and two open-source graphical user interfaces (GUIs) were developed. Those interfaces can be adapted front-end as well as back-end, ensuring a holistic comprehension of their capabilities and limits. As a result, a six-layer architecture, from digitization to an interactive project management tool, was designed and implemented in the practical workflow at the academic institution. To take the complexity of thermo-mechanical processing in the metal processing field into account, an alternative layer, connected with the thermo-mechanical treatment simulator Gleeble 3800, was designed. This framework is capable of transferring sensor data with high frequency, enabling data collection for the numerical simulation of complex material behavior under high temperature processing. Finally, the possibility of connecting both systems by using open-source software packages is demonstrated.


2021 ◽  
Vol 640 (4) ◽  
pp. 042014
Author(s):  
E N Turin ◽  
A N Susskiy ◽  
R S Stukalov ◽  
M V Shestopalov ◽  
E L Turina ◽  
...  
Keyword(s):  
Low Cost ◽  

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2254
Author(s):  
Francisco Javier González-Cañete ◽  
Eduardo Casilari

Over the last few years, the use of smartwatches in automatic Fall Detection Systems (FDSs) has aroused great interest in the research of new wearable telemonitoring systems for the elderly. In contrast with other approaches to the problem of fall detection, smartwatch-based FDSs can benefit from the widespread acceptance, ergonomics, low cost, networking interfaces, and sensors that these devices provide. However, the scientific literature has shown that, due to the freedom of movement of the arms, the wrist is usually not the most appropriate position to unambiguously characterize the dynamics of the human body during falls, as many conventional activities of daily living that involve a vigorous motion of the hands may be easily misinterpreted as falls. As also stated by the literature, sensor-fusion and multi-point measurements are required to define a robust and reliable method for a wearable FDS. Thus, to avoid false alarms, it may be necessary to combine the analysis of the signals captured by the smartwatch with those collected by some other low-power sensor placed at a point closer to the body’s center of gravity (e.g., on the waist). Under this architecture of Body Area Network (BAN), these external sensing nodes must be wirelessly connected to the smartwatch to transmit their measurements. Nonetheless, the deployment of this networking solution, in which the smartwatch is in charge of processing the sensed data and generating the alarm in case of detecting a fall, may severely impact on the performance of the wearable. Unlike many other works (which often neglect the operational aspects of real fall detectors), this paper analyzes the actual feasibility of putting into effect a BAN intended for fall detection on present commercial smartwatches. In particular, the study is focused on evaluating the reduction of the battery life may cause in the watch that works as the core of the BAN. To this end, we thoroughly assess the energy drain in a prototype of an FDS consisting of a smartwatch and several external Bluetooth-enabled sensing units. In order to identify those scenarios in which the use of the smartwatch could be viable from a practical point of view, the testbed is studied with diverse commercial devices and under different configurations of those elements that may significantly hamper the battery lifetime.


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