Relevant bibliographies by topics / Leap motion sensor

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  1. Journal articles
  2. Dissertations / Theses
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  5. Conference papers

Academic literature on the topic 'Leap motion sensor'

Author: Grafiati
Published: 4 June 2021
Last updated: 17 February 2022

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Journal articles on the topic "Leap motion sensor"

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Fernando, Redondo, Supria Supria, and Muhamad Nasir. "AplikasiMarawis Digital Menggunakan Sensor Leap Motion." INOVTEK Polbeng - Seri Informatika 2, no. 2 (2017): 141. http://dx.doi.org/10.35314/isi.v2i2.201.

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Intisari - Marawis adalah salah satu jenis "band tepuk” dengan perkusi sebagai alat musik utamanya. Musik ini merupakan kolaborasi antara kesenian Timur Tengah dan Betawi, dan memiliki unsur keagamaan yang kental. Itu tercermin dari berbagai lirik lagu yang dibawakan yang merupakan pujian dan kecintaan kepada Sang Pencipta. Pada saat ini memainkan alat musik marawis masih dengan cara manual dengan cara memukul alat musik marawis tersebut dengan sekuat mungkin dan membutuhkan banyak tenaga, dan lama kelamaan tangan akan terasa sakit. Untuk mengatasi masalah tersebut maka di usulkan Aplikasi Marawis Digital Menggunakan Sensor Leap Motion. Aplikasi dibuat dengan Leap Motion untuk mendeteksi titik-titk koordinat tangan pengguna. Untuk menghasilkan dua suara marawis yang berbeda maka di buat mapping area untuk menentukan suara 1 dan suara 2. Aplikasi ini dapat menjadi alternative untuk memainkan alat musik marawis. Dari hasil uji coba yang dilakukan menunjukkan bahwa aplikasi ini mampu menggantikan penggunaan tenaga manusia ke teknik digital. Kata Kunci : Leap Motion, Aplikasi Desktop, Marawis
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Sousa, L., J. Monteiro, P. J. S. Cardoso, and J. M. F. Rodrigues. "Natural user interface based on gestures recognition using Leap Motion sensor." Dos Algarves: a Multidisciplinary e-journal 26, no. 1 (2015): 107–21. http://dx.doi.org/10.18089/damej.2015.26.1.6.

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Jadhav, Siddhant A., Rohan R. Yashod, Aditya P. Sabne, Yash K. Rokde, and Chandrabhan R. Ghuge. "Leap Motion Sensor Technology Based Robo-Control System." International Journal of Computer Science and Mobile Computing 9, no. 12 (2020): 50–58. http://dx.doi.org/10.47760/ijcsmc.2020.v09i12.007.

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Jadhav, Siddhant A., Rohan R. Yashod, Aditya P. Sabne, Yash K. Rokde, and Chandrabhan R. Ghuge. "Leap Motion Sensor Technology Based Robo-Control System." International Journal of Computer Science and Mobile Computing 9, no. 12 (2020): 50–58. http://dx.doi.org/10.47760/ijcsmc.2020.v09i12.007.

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Nizamis, Kostas, Noortje Rijken, Ana Mendes, Mariska Janssen, Arjen Bergsma, and Bart Koopman. "A Novel Setup and Protocol to Measure the Range of Motion of the Wrist and the Hand." Sensors 18, no. 10 (2018): 3230. http://dx.doi.org/10.3390/s18103230.

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The human hand is important for the performance of activities of daily living which are directly related to quality of life. Various conditions, such as Duchenne muscular dystrophy (DMD) can affect the function of the human hand and wrist. The ability to assess the impairment in the hand and the wrist by measuring the range of motion (ROM), is essential for the development of effective rehabilitation protocols. Currently the clinical standard is the goniometer. In this study we explore the feasibility and reliability of an optical sensor (Leap motion sensor) in measuring active hand/wrist ROM. We measured the hand/wrist ROM of 20 healthy adults with the goniometer and the Leap motion sensor, in order to check the agreement between the two methods and additionally, we performed a test-retest of the Leap motion sensor with 12 of them, to assess its reliability. The results suggest low agreement between the goniometer and the leap motion sensor, yet showing a large decrease in measurement time and high reliability when using the later. Despite the low agreement between the two methods, we believe that the Leap motion sensor shows potential to contribute to the development of hand rehabilitation protocols and be used with patients in a clinical setting.
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Supria, Supria, Depandi Enda, and Muhamad Nasir. "Pengenalan Bentuk Tangan secara Real Time Menggunakan Leap Motion dan K-Nearest Neighbors sebagai Sistem Kendali Robot Beroda." CESS (Journal of Computer Engineering, System and Science) 5, no. 2 (2020): 178. http://dx.doi.org/10.24114/cess.v5i2.18141.

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Sistem kendali robot saat ini telah banyak dibuat dengan menggunakan berbagai metode seperti sensor accelerometer, sensor suara, leap motion. Pada penelitian ini diusulkan pengenalan bentuk tangan secara real time menggunakan leap motion dan K-Nearest Neighbors (KNN) sebagai sistem kendali robot beroda. Leap motion digunakan untuk mendeteksi titik koordinat posisi tangan pada pandangan leap motion. pembentukan fitur dilakukan dengan mengukur jarak euclidean distance antara palm position dengan finger tip. KNN digunakan untuk menentukan kelas pada data testing. Uji coba dilakukan menggunakan tangan penulis dengan 5 jenis instruksi yaitu maju, mundur, stop, belok kanan, belok kiri dan setiap instruksi di ujicoba sebanyak 20 kali percobaan. Dari hasil ujicoba yang dilakukan menunjukkan bahwa sistem yang diusulkan memiliki tingkat akurasi pengenalan 94%.
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Behera, Santosh Kumar, Debi Prosad Dogra, and Partha Pratim Roy. "Analysis of 3D signatures recorded using leap motion sensor." Multimedia Tools and Applications 77, no. 11 (2017): 14029–54. http://dx.doi.org/10.1007/s11042-017-5011-4.

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Nugraha, Syaiful, Darlis Heru Murti, and Wijayanti Nurul Khotimah. "Penggunaan Dual Sensor Leap Motion Controller untuk Sistem Isyarat Bahasa Indonesia (SIBI)." INFORMAL: Informatics Journal 4, no. 2 (2019): 48. http://dx.doi.org/10.19184/isj.v4i2.12634.

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Bahasa isyarat adalah bahasa yang dibentuk dengan kombinasi gerakan jari, tangan, tubuh serta ekspresi wajah yang digunakan oleh para penyandang disabilitas seperti tunarungu dan tunawicara. Salah satu pengenalan bahasa isyarat tersebut adalah pengenalan dengan menggunakan teknologi sensor Leap Motion Controller (LMC). Akan tetapi pada penerapannya, sensor LMC tidak selalu dapat mengenali semua jari dengan baik. Hal ini dikarenakan pembentukan dari bahasa isyarat yang saling bersentuhan antar jari, jari yang dilipat, tersembunyi ataupun terhalang oleh jari lainnya. Sehingga pada penelitian ini diusulkan penggunaan dual sensor LMC yang bertujuan untuk mencegah dan meminimalisir adanya kesalahan dalam mengenal bahasa isyarat dari jari yang dibentuk. Tahapan proses yang dilakukan adalah mendesain tata letak sensor LMC dan mengkombinasikan data fitur dari masing-masing sensor LMC baik yang bersifat statis dan dinamis yang kemudian diklasifikasikan menggunakan metode L-GCNN. Dari hasil pengujian yang dilakukan, penggunaan dual sensor LMC ini dapat mengenal isyarat SIBI yang diberikan. Skema yang terbaik adalah dengan mengacu pada tata letak multi sensor yang saling berhadapan membentuk sudut 120 derajat dengan tingkat akurasi sebesar 86,42%, dengan rata-rata akurasi dari keseluruhan skenario sebesar 84,36%. Adanya desain tata letak sensor LMC dan kombinasi penggabungan data fitur masing-masing sensor dapat meningkatkan akurasi pengenalan dengan rata-rata peningkatan mencapai 5,35%.
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Kumar, Pradeep, Rajkumar Saini, Partha Pratim Roy, and Debi Prosad Dogra. "Study of Text Segmentation and Recognition Using Leap Motion Sensor." IEEE Sensors Journal 17, no. 5 (2017): 1293–301. http://dx.doi.org/10.1109/jsen.2016.2643165.

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Sun, Xinyao, Anup Basu, and Irene Cheng. "Multi-Sensor Motion Fusion Using Deep Neural Network Learning." International Journal of Multimedia Data Engineering and Management 8, no. 4 (2017): 1–18. http://dx.doi.org/10.4018/ijmdem.2017100101.

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Hand pose estimation for a continuous sequence has been an important topic not only in computer vision but also human-computer-interaction. Exploring the feasibility to use hand gestures to replace input devices, e.g., mouse, keyboard, joy-stick and touch screen, has attracted increasing attention from academic and industrial researchers. The fast advancement of hand pose estimation techniques is complemented by the rapid development of smart sensors technology such as Kinect and Leap. We introduce a hand pose estimation multi-sensor system. Two tracking models are proposed based on Deep (Recurrent) Neural Network (DRNN) architecture. Data captured from different sensors are analyzed and fused to produce an optimal hand pose sequence. Experimental results show that our models outperform previous methods with better accuracy, meeting real-time application requirement. Performance comparisons between DNN and DRNN, spatial and spatial-temporal features, and single- and dual- sensors, are also presented.
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Dissertations / Theses on the topic "Leap motion sensor"

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Felippsen, Eduardo Alberto. "Aplicação do sensor leap motion como instrumento didático no ensino de crianças surdas." Universidade Estadual do Oeste do Paraná, 2017. http://tede.unioeste.br/handle/tede/3137.

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Submitted by Miriam Lucas (miriam.lucas@unioeste.br) on 2017-11-08T17:58:36Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Eduardo_Alberto_Felippsen_2017.pdf: 2829878 bytes, checksum: 34245de5c475cba9de58a5835f5abfd4 (MD5)<br>Made available in DSpace on 2017-11-08T17:58:36Z (GMT). No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Eduardo_Alberto_Felippsen_2017.pdf: 2829878 bytes, checksum: 34245de5c475cba9de58a5835f5abfd4 (MD5) Previous issue date: 2017-02-03<br>The technologies are in broad development and increasingly present in the students' daily life, a reality that can be appropriated by the school for the creation of new teaching strategies. In the case of teaching deaf children, the use of technologies may be even more effective, since the visual aspect should be privileged. In this context, this dissertation presents, by means of a qualitative research with action-research methodology, the application of the Leap Motion Gesture Interaction Interface in classes for deaf children. The planning and selection of the softwares took place together, involving the researcher and the teachers of the Training Center of the Professionals of the Education and Assistance to Persons with Deafness (in Portuguese, Centro de Capacitação dos Profissionais da Educação e Atendimento às Pessoas com Surdez) in the city of Cascavel / PR, this, in the generation of lesson plans. It was identified that the communication and mediation of the teacher are key-factors for the student to interpret and understand the interaction environment, as well as the task that is expected to be realized. This, because the student is in training in the Brazilian Sign Language (in Portuguese, Língua Brasileira de Sinais - Libras) and hasn’t knowledge of the written Portuguese language. In other words, there is a strong dependence of the teacher to that him/her interprets the interface of the software and translates it to Libras, inserting in this translation elements that result in the understanding by the child. As results, it was verified that, in well-planned use scenarios, there was the contribution of the use of the Leap Motion sensor in the learning, and that there was a significant contribution in the social interaction and the collaboration between the students in the accomplishment of the tasks. These aspects of interaction among students can be also considered in the elaboration of new teaching strategies supported by gestural interfaces.<br>As tecnologias estão em franco desenvolvimento, e cada vez mais presentes no cotidiano dos estudantes, uma realidade que pode ser apropriada pela escola para a criação de novas estratégias de ensino. No caso do ensino de crianças surdas, o uso de tecnologias pode ser ainda mais efetivo, uma vez o aspecto visual deve ser privilegiado. Neste contexto, esta dissertação apresenta, por meio de uma pesquisa qualitativa com metodologia de pesquisa-ação, a aplicação da Interface de Interação Gestual Leap Motion em aulas para crianças surdas. O planejamento e escolha dos softwares foi conjunto, envolvendo o pesquisador e os professores do Centro de Capacitação dos Profissionais da Educação e Atendimento às Pessoas com Surdez na cidade de Cascavel/PR, isto, na geração de planos de aula. Identificou-se que a comunicação e a mediação do professor são fatores-chave para que o aluno possa interpretar e compreender o ambiente de interação, bem como a tarefa que se espera seja realizada. Isto, pois o aluno encontra-se em formação na Língua Brasileira de Sinais (Libras) e não possui conhecimento da Língua Portuguesa escrita. Em outras palavras, há uma forte dependência do professor para que este interprete a interface do software e a traduza para Libras, inserindo nesta tradução elementos que resultem na compreensão por parte da criança. Como resultados, verificou-se que, em cenários de uso bem planejados, houve a contribuição do uso do sensor Leap Motion no aprendizado, e que houve contribuição significativa na interação social e na colaboração entre os alunos na realização das tarefas. Esses aspectos de interação entre os estudantes podem ser também considerados na elaboração de novas estratégias de ensino suportadas por interfaces gestuais.
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Kincaid, Clay Jordan. "The Feasibility of Using a Markerless Motion Capture Sensor (Leap MotionTM Controller) forQuantitative Motor Assessment Intended for a Clinical Setting." BYU ScholarsArchive, 2016. https://scholarsarchive.byu.edu/etd/6262.

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Although upper limb motor impairments are common, the primary tools for assessing and tracking these impairments in a clinical setting are subjective, qualitative rating scales that lack resolution and repeatability. Markerless motion capture technology has the potential to greatly improve clinical assessment by providing quick, low-cost, and accurate tools to objectively quantify motor deficits. Here we lay some of the groundwork necessary to enable markerless motion capture systems to be used in clinical settings. First, we adapted five motor tests common in clinical assessments so they can be administered via markerless motion capture. We implemented these modified tests using a particular motion capture sensor (Leap MotionTM Controller, hereafter referred to as the Leap Motion sensor) and administered the tests to 100 healthy subjects to evaluate the feasibility of administrating these tests via markerless motion capture. Second, to determine the ability of the Leap Motion sensor to accurately measure tremor, we characterized the frequency response of the Leap Motion sensor. During the administration of the five modified motor tests on 100 healthy subjects, the subjects had little trouble interfacing with the Leap Motion sensor and graphical user interface, performing the tasks with ease. The Leap Motion sensor maintained an average sampling rate above 106 Hz across all subjects during each of the five tests. The rate of adverse events caused by the Leap Motion sensor (mainly jumps in time or space) was generally below 1%. In characterizing the frequency response of the Leap Motion sensor, we found its bandwidth to vary between 1.7 and 5.5 Hz for actual tremor amplitudes above 1.5 mm, with larger bandwidth for larger amplitudes. To improve the accuracy of tremor measurements, we provide the magnitude ratios that can be used to estimate the actual amplitude of the oscillations from the measurements by the Leap Motion sensor. These results suggest that markerless motion capture systems are on the verge of becoming suitable for routine clinical use, but more work is necessary to further improve the motor tests before they can be administered via markerless motion capture with sufficient robustness for clinical settings.
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Rakesh, Sumit. "Exploiting Leap Motion and Microsoft Kinect Sensors for Static and Dynamic Sign Gesture Recognition." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-87296.

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One of the primary ways of communication between humans is verbal communication. Among hearing-impaired persons, the traditional way of communication is through sign language. Sign gestures are the atomic actions used in sign language for non-verbal communication. With the advancement in both sensor-based devices and machine learning techniques, there is a lot of scope in identifying and developing an efficient, robust, and low-cost sign gesture recognition system that can help hearing-impaired individuals to communicate among themselves and people with usual hearing ability. My focus will be on classical machine learning algorithms for static the recognition of sign gestures recorded using leap motion sensors, and deep learning methods for the recognition of dynamic sign gestures recorded using Microsoft Kinect sensors. I addressed the Leap motion-based static palm sign gesture recognition by applying three machine learning algorithms: Support Vector Machine (SVM), Random Forest (RF), and Naive Bayes (NB), and used Genetic Algorithm (GA) for feature selection. Genetically selected features are fed to different classifiers for gesture recognition. Whereas, we addressed the Microsoft Kinect-based dynamic sign gesture recognition using an end-to-end deep learning approach. The dynamic sign gestures are sequential that deep learning methods are proven to model effectively without handcrafted features. Deep learning models can directly work on raw data and learn higher-level representations (features) by themselves. To test our hypothesis, we have used two latest and promising deep learning models, Gated Recurrent Unit (GRU) and Bidirectional Long Short-Term Memory (BiLSTM), and trained them using only raw data for dynamic gestures; the dynamic gestures were collected from three views namely front, mid, side views. With regard to static palm sign gesture recognition, an accuracy of 74.00% is recorded with RF classifier on the Leap motion sign gesture dataset. With regard to dynamic sign gesture recognition, we have performed comparative analysis among both models and also with the base paper results. Conducted experiments reflected that the proposed method outperforms the existing work, where GRU successfully concluded with 70.78% average accuracy with front view training.
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Karimi, Majid. "Master ’s Programme in Information Technology: Using multiple Leap Motion sensors in Assembly workplace in Smart Factory." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-32392.

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The new industry revolution creates a vast transformation in the manufacturing methods. Embedded Intelligence and communication technologies facilitate the execution of the smart factory. It can provide lots of features for strong customization of products. Assembly system is a critical segment of the smart factory. However, the complexity of production planning and the variety of products being manufactured, persuade the factories to use different methods to guide the workers for unfamiliar tasks in the assembly section. Motion tracking is the process of capturing the movement of human body or objects which has been used in different industrial systems. It can be integrated to a wide range of applications such as interacting with computers, games and entertainment, industry, etc. Motion tracking can be integrated to assembly systems and it has the potential to create an improvement in this industry as well. But the integration of motion tracking in industrial processes is still not widespread. This thesis work provides a fully automatic tracking solution for future systems in manufacturing industry and other fields. In general a configurable, flexible, and scalable motion tracking system is created in this thesis work to amend the tracking process. According to our environment, we have done a research between different motion tracking methods and technologies including Kinect and Leap Motion sensor, and finally the leap motion sensor is selected as the most appropriate method, because it fulfils our demands in this project. Multiple Leap motion sensors are used in this work to cover areas with different size. Data fusion between multiple leap motion sensors can be considered as another novel contribution of this thesis work. To achieve this goal data from multiple sensors are combined. This system can improve the lack of accuracy in order to creating a practical industrial application. By fusion of several sensors in order to achieve accuracies that allow implementation in practice, a motion tracking system with higher accuracy is created.
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Tummalapally, Subhadra. "Augment the Multi-Modal Interaction Capabilities of HoloLens Through Networked Sensory Devices." Wright State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=wright154756489614826.

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Boberg, Arvid. "Virtual lead-through robot programming : Programming virtual robot by demonstration." Thesis, Högskolan i Skövde, Institutionen för ingenjörsvetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-11403.

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This report describes the development of an application which allows a user to program a robot in a virtual environment by the use of hand motions and gestures. The application is inspired by the use of robot lead-through programming which is an easy and hands-on approach for programming robots, but instead of performing it online which creates loss in productivity the strength from offline programming where the user operates in a virtual environment is used as well. Thus, this is a method which saves on the economy and prevents contamination of the environment. To convey hand gesture information into the application which will be implemented for RobotStudio, a Kinect sensor is used for entering the data into the virtual environment. Similar work has been performed before where, by using hand movements, a physical robot’s movement can be manipulated, but for virtual robots not so much. The results could simplify the process of programming robots and supports the work towards Human-Robot Collaboration as it allows people to interact and communicate with robots, a major focus of this work. The application was developed in the programming language C# and has two different functions that interact with each other, one for the Kinect and its tracking and the other for installing the application in RobotStudio and implementing the calculated data into the robot. The Kinect’s functionality is utilized through three simple hand gestures to jog and create targets for the robot: open, closed and “lasso”. A prototype of this application was completed which through motions allowed the user to teach a virtual robot desired tasks by moving it to different positions and saving them by doing hand gestures. The prototype could be applied to both one-armed robots as well as to a two-armed robot such as ABB’s YuMi. The robot's orientation while running was too complicated to be developed and implemented in time and became the application's main bottleneck, but remained as one of several other suggestions for further work in this project.
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Casanova, Lorenzo. "Il senso di presenza nelle realtà virtuali vissute tramite HMD: l'interazione e le interfacce." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/8366/.

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Grazie alla crescente evoluzione tecnologica è oggi possibile, tramite Head Mounted Display (HMD), vivere una realtà virtuale ricca nei dettagli, interattiva ed immersiva. L’avanzamento in questo settore ha infatti portato a una vera e propria rivoluzione, aprendo la possibilità di utilizzare questa tecnologia in molteplici ambiti. L’ostacolo riscontrato è che a un progresso di tale entità non si associa un adeguato aggiornamento e perfezionamento riguardo alle metodologie di interazione con oggetti 3D, dell’utilizzo di interfacce grafiche e del generale design ambientale. La diretta conseguenza di questo mancato aggiornamento è quella di indebolire o addirittura annullare l’effetto presenza dell'HMD, requisito indispensabile che consente all’utente di immergersi sensorialmente nel contesto simulato. L’obiettivo di questo studio consiste nel comprendere cosa è necessario tenere in considerazione e quali regole vanno cambiate per poter mantenere un'alta sensazione di presenza per l'utente all’interno di una realtà virtuale. A questo scopo è stato creato un ambiente virtuale 3D in grado di supportare l'utilizzo di un HMD, l'Oculus Rift, e di diversi dispositivi di input in grado di consentire controllo tramite movimenti naturali, il Razer Hydra ed il Leap Motion, in modo da poter effettuare un'analisi diretta sul livello del fattore presenza percepito nell'effettuare diverse interazioni con l'ambiente virtuale e le interfacce grafiche attraverso questi dispositivi. Questa analisi ha portato all'individuazione di molteplici aspetti in queste tipologie di interazioni e di design di intrefacce utente che, pur essendo di uso comune negli ambienti 3D contemporanei, se vissuti in un contesto di realtà virtuale non risultano più funzionali e indeboliscono il senso di presenza percepito dall'utente. Per ognuno di questi aspetti è stata proposta ed implementata una soluzione alternativa (basata su concetti teorici quali Natural Mapping, Diegesis, Affordance, Flow) in grado di risultare funzionale anche in un contesto di realtà virtuale e di garantire una forte sensazione di presenza all'utente. Il risultato finale di questo studio sono quindi nuovi metodi di design di ambienti virtuali per realtà aumentata. Questi metodi hanno permesso la creazione di un ambiente virtuale 3D pensato per essere vissuto tramite HMD dove l'utente è in grado di utilizzare movimenti naturali per interagire con oggetti 3D ed operare interfacce grafiche.
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Bizarro, João Pedro Pereira. "Interfaces gestuais baseados no controlador Leap Motion." Master's thesis, 2018. http://hdl.handle.net/10400.26/36452.

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In the present, most of the human-machine interactions are based on the use of peripherals such as keyboard and computer mouse. However, the use of such peripherals can create certain limitations in the way people interact with machines, for this reason, there is a need to create natural interfaces. One of the possible approaches that has been proposed involves performing gestures that are recognized by a sensor and interpreted by the computer. The use of hands on a human-machine interface is justified by the fact that the hands are an important element in nonverbal communications. Due to this, in this project several possible gesture interfaces were analyzed, using the Leap Motion sensor. The project was based on the development of methods that allowed the recognition of gestures and their association to an action that the computer should perform. Through the analysis of existing studies in the area and the various methods used to allow a program to classify a data set, a gesture classification system was developed. The classification system has tested to verify its accuracy and precision. Using the knowledge obtained throughout the project, and as proof of concept, an application was developed to demonstrate the usefulness of the classification system in a real situation. This application can recognize a gesture and associate it with a keyboard key, allowing a user to write the message resulting from the gestures he makes. This project main conclusion was that the gesture classification system trained using SVM can make a good separation of the various gestures and with this classify correctly the gestures. Most of problems that arise during the recognition of a gesture are a consequence of the Leap Motion not being able to track correctly the gesture being made.
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Chen, Hung-Yang, and 陳弘洋. "A Study of Industrial Robot Calibration Using LEAP MOTION Sensor." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/99077346944054250819.

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碩士<br>國立中興大學<br>機械工程學系所<br>103<br>This thesis is focusing on kinematic parameter calibration of industrial robot using LEAP MOTION sensor (model number LM-010) as measurement device. The sensor has several advantages, such as low cost, small, easy to use and open code, etc. In short, the point of this thesis is to evaluate a way of low cost, and contactless sensor for calibrating industrial robot kinematic parameter. The level of this calibration is defined 2nd –level calibration. To calibrate robot, Denavit-Hartenberg (D-H) method has been used as forward kinematic model, Geometric approach as inverse kinematic model and LEAP MOTION sensor as measuring device. After measuring, least square method has been used to identified errors in kinematic parameter and fake pose method to calibrate in angle of revolute joints. In the end, ISO9283:1998 is used to check the result after calibration and compensation. Before calibration, ISO9283:1998 has been used to check pose accuracy of the robot in five measuring point and thirty cycles in 60mm3 cube, and the result is 0.34mm. Kinematic parameters have been simulated and estimated in MATLAB software. The simulation result has proven the feasibility of this proposed method that using least square method to estimated kinematic parameters and fake pose method to compensate in angles of revolute joints. Although nominal measuring repeatability of the leap motion sensor is claimed to be 0.01mm, but it has been found that the experimental results have much worse value especially when measuring position in the Y direction in farther positions. In linearity, X and Z direction has maximum deviation about 1.00mm, and 2.50mm in Y direction. The proposed least square method has failed to estimate robot kinematic parameters because the computational results is not reasonable. The reasons may be from the setting error of the measuring device or from the not enough repeatability of the leap motion sensors or getting unreasonable solution even it was convergence.
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Hráský, Pavel. "Pohybové programy pro ovlivnění tělesného složení a tělesné zdatnosti seniorů." Doctoral thesis, 2014. http://www.nusl.cz/ntk/nusl-336122.

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In this work we focused on the application of physical activity, which aimed to reduce the negative impact of physical deprivation and associated functional and structural changes in the musculoskeletal system. The principal criterion was the diagnosis of the organ systems of the locomotor system, focusing on the muscular system. The subsequent application of appropriate forms of exercise intervention was designed to mitigate the effects of the aging process and functional changes in the body of the senior individual. Finally, we wanted to assess the impact of changes in body composition in its own self- sufficiency and independence of older people and the quality of life of older people in terms of physical and psychosocial aspects. The most significant is the loss of muscle mass, sarcopenia development, increase fat mass with frequent reductions in body weight. The focus of our work and its specific purpose is to clarify the influence of the applied physical interventions. To assess changes in body composition are needed for our work used the method of multi Bioanalysis. Results in body composition in older adults have been evaluated and intra-individual measured data were compared with the general senior population. Kinesiology testing shortened muscle groups was carried out repeatedly to reduce...
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Books on the topic "Leap motion sensor"

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Shaibani, Aziz. Gait Disorders. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199898152.003.0001.

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Gait is a complicated process that is initiated and maintained by different mechanisms, neurological including neuromuscular, and non-neurological including musculoskeletal. Neuromuscular clinics receive referrals about patients who may have non-neuromuscular disorders such as Parkinsondisease, focal foot dystonia, and multiple sclerosis. It is important for a neuromuscular specialist to be aware of other gait disorders. Important neuromuscular disorders of gait include neuropathies (foot drop, sensory ataxia), myopathies, muscle stiffness and spasms, myotonia, and motor neuron disease. Functional gait disorder comprises a significant entity that may lead to extensive non-necessary investigations that can be saved if the specialist is aware of these symptoms.
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Shaibani, Aziz. Gait Disorders. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190661304.003.0001.

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Gait is a complicated process that is initiated and maintained by different mechanisms, both neurological (including neuromuscular) and nonneurological (including musculoskeletal). Neuromuscular clinics receive referrals about patients who may have nonneuromuscular disorders such as Parkinson disease, focal foot dystonia, and multiple sclerosis (MS). It is important for neuromuscular specialists to be aware of other gait disorders as well. Important neuromuscular disorders of gait include neuropathies (foot drop, sensory ataxia), myopathies, muscle stiffness and spasms, myotonia, and motor neuron disease. Functional gait disorder comprises a significant entity that may lead to extensive, unnecessary investigations that can be saved if the specialist is aware of the characteristic features of these symptoms.
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Mochel, Fanny. Spastic Paraplegia Type 5. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199972135.003.0041.

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Spastic paraplegia type 5 (SPG5) is an autosomal recessive hereditary spastic paraplegia due to mutations in CYP7B1, which encodes oxysterol 7α‎-hydroxylase. Oxysterol 7α‎-hydroxylase is involved in the synthesis of bile acids from cholesterol. CYP7B1 mutations are responsible for rare forms of liver failure in infancy as well as lower motor neuron degeneration in adults with no obvious genotype-phenotype correlation. SPG5 is mostly characterized by spastic paraplegia with prominent posterior column sensory impairment that can lead to sensory ataxia and bladder dysfunction. SPG5 can easily be diagnosed thanks to the significant elevation of two plasma oxysterols: 27- and 25-hydroxycholesterol. Accordingly, plasma oxysterols are biomarkers that should be included in the screening of any spastic paraplegia of unknown etiology. Furthermore, the dramatic therapeutic response of a child with liver failure due to CYP7B1 mutations using chenodeoxycholic acid opens promising therapeutic perspectives for SPG5 patients, possibly as in cerebrotendinous xanthomatosis.
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Zimmermann, Thomas Ede. Fregean Compositionality. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198739548.003.0010.

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Two distinctive features of Frege’s approach to compositionality are reconstructed in terms of the theory of extension and intension: (i) its bias in favour of extensional operations; and (ii) its resort to indirect senses in the face of iterated opacity. While (i) has been preserved in current formal semantics, it proves to be stronger than a straightforward extensionality requirement in terms of Logical Space, the difference turning on a subtle distinction between extensions at particular points and extensions per se. (ii) has traditionally been dismissed as redundant, and is shown to lead to a mere ‘baroque’ reformulation of ordinary compositionality. Nevertheless, whatever Frege’s motive, the very idea of having opaque denotations keep track of the depth of their embedding gives rise to a fresh view at certain scope paradoxes that had previously been argued to lie outside the reach of a binary distinction between extension and intension.
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Pettit, Philip. Committing to Others. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190904913.003.0005.

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We in Erewhon will have the means, the motive and the confidence to avow many of our beliefs. A means of avowing the belief that p is to assert that p, since this forecloses the misleading-mind excuse. A motive for doing so is that the communication thereby becomes more expensive and more credible; I deny myself a way of getting off the hook in the event of a miscommunication: viz., by claiming I must have misread my own mind. And the confidence required is supplied by the fact that I can consciously make up my mind on various issues by consulting the data and seeing where they lead me; I do not have to resort to introspective self-scanning. By parallel arguments we in Erewhon will be led to avow not only beliefs but also desires and intentions, relying on desiderata to play a role analogous to that of data in the case of beliefs. And we will be led by the same token to pledge various intentions—and intentions only—foreclosing the possibility of changing our mind as well as the possibility of having been misled about our minds. Avowals and pledges of these kinds are commitments in the non-moral, game-theory sense: they represent wagers in which we stake our reputations on living up to our words.
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Book chapters on the topic "Leap motion sensor"

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Hassan, Md Adib, Qazi Shadman, Mishkat Haider Chowdhury, Sakib Al Hasan, and Jia Uddin. "User Authentication Using Password and Hand Gesture with Leap Motion Sensor." In Lecture Notes on Data Engineering and Communications Technologies. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4968-1_2.

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Lupinetti, Katia, Andrea Ranieri, Franca Giannini, and Marina Monti. "3D Dynamic Hand Gestures Recognition Using the Leap Motion Sensor and Convolutional Neural Networks." In Lecture Notes in Computer Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58465-8_31.

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Demircioğlu Kam, Burçak, and Hatice Köse. "A New Data Collection Interface for Dynamic Sign Language Recognition with Leap Motion Sensor." In Springer Series in Design and Innovation. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65060-5_28.

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Sun, Xinyao, Anup Basu, and Irene Cheng. "Multi-Sensor Motion Fusion Using Deep Neural Network Learning." In Deep Learning and Neural Networks. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0414-7.ch032.

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Hand pose estimation for a continuous sequence has been an important topic not only in computer vision but also human-computer-interaction. Exploring the feasibility to use hand gestures to replace input devices, e.g., mouse, keyboard, joy-stick and touch screen, has attracted increasing attention from academic and industrial researchers. The fast advancement of hand pose estimation techniques is complemented by the rapid development of smart sensors technology such as Kinect and Leap. We introduce a hand pose estimation multi-sensor system. Two tracking models are proposed based on Deep (Recurrent) Neural Network (DRNN) architecture. Data captured from different sensors are analyzed and fused to produce an optimal hand pose sequence. Experimental results show that our models outperform previous methods with better accuracy, meeting real-time application requirement. Performance comparisons between DNN and DRNN, spatial and spatial-temporal features, and single- and dual- sensors, are also presented.
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Coffey, Aodhán L., and Tomás E. Ward. "Combined Ambient and Wearable Sensors for Gesture-Based Environmental Control in the Home." In Recent Advances in Ambient Intelligence and Context-Aware Computing. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-7284-0.ch001.

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Home-based therapy will need to play a huge role in the future if we are to achieve effective and cost-efficient forms of rehabilitation. Creative solutions are already being implemented by researchers with the development of revolutionary applications for healthcare leveraging commercially available technology. In this chapter, the authors endeavour to contribute to this goal, describing their ongoing contributions through the application of combined ambient and wearable sensors for gesture-based environmental control. The authors describe in detail the development of three novel systems: an autonomous sensor glove that classifies hand gestures and controls Infrared (IR)-based devices, a smart watch that recognises motion gestures to interact with Radio Frequency (RF) controlled devices, and a hybrid (sensor glove and LEAP motion controller) sensor solution for achieving high fidelity hand and finger motion capture/playback with applications for virtual ambient systems.
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Souza, Marcus Romano Salles Bernardes de, Eduardo Apolinário Lopes, and Rogério Sales Gonçalves. "AVALIAÇÃO DA EXATIDÃO E REPETIBILIDADE DO SENSOR LEAP MOTION CONTROLLER PARA A SUA UTILIZAÇÃO EM REABILITAÇÃO VIRTUAL." In Pesquisa Científica e Inovação Tecnológica nas Engenharias 2. Atena Editora, 2019. http://dx.doi.org/10.22533/at.ed.03520060112.

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Charry, Edgar, and Daniel T. H. Lai. "Methods for Improving Foot Displacement Measurements Calculated from Inertial Sensors." In Biomedical Engineering and Information Systems. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-61692-004-3.ch005.

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The use of inertial sensors to measure human movement has recently gained momentum with the advent of low cost micro-electro-mechanical systems (MEMS) technology. These sensors comprise accelerometer and gyroscopes which measure accelerations and angular velocities respectively. Secondary quantities such as displacement can be obtained by integration of these quantities, a method which presents challenging issues due to the problem of accumulative sensor errors. This chapter investigates the spectral evaluation of individual sensor errors and looks at the effectiveness of minimizing these errors using static digital filters. The primary focus is on the derivation of foot displacement data from inertial sensor measurements. The importance of foot, in particular toe displacement measurements is evident in the context of tripping and falling which are serious health concerns for the elderly. The Minimum Toe Clearance (MTC) as an important gait variable for falls-risk prediction and assessment, and therefore the measurement variable of interest. A brief sketch of the current devices employing accelerometers and gyroscopes is presented, highlighting the problems and difficulties reported in literature to achieve good precision. These have been mainly due to the presence of sensor errors and the error accumulative process employed in obtaining displacement measurements. The investigation first proceeds to identify the location of these sensor errors in the frequency domain using the Fast Fourier Transform (FFT) on raw inertial sensor data. The frequency content of velocity and displacement measurements obtained from integrating the inertial data using a well known strap-down method is then explored. These investigations revealed that large sensor errors occurred mainly in the low frequency spectrum while white noise exists in all frequency spectra. The efficacy of employing a band-pass filter to remove a large portion of these errors and their effect on the derived displacements is elaborated on. The cross-correlation of the FFT power spectra from a highly accurate optical measurement system and processed sensor data is used as a metric to evaluate the performance of the band-pass filter at several stages of the processing stage. The motivation is that a more fundamental method would require less computational demand and could lead to more efficient implementations in low-power and systems with limited resources, so that portable sensor based motion measurement system would provide a good degree of measurement accuracy.
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Cardoso, Pedro, João Rodrigues, Jânio Monteiro, and Luís Sousa. "Using a Hands-Free System to Manage Common Devices in Constrained Conditions." In Handbook of Research on Human-Computer Interfaces, Developments, and Applications. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-5225-0435-1.ch004.

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As computing equipment become ubiquitous, a new set of interfacing devices need to be developed and properly adapted to the conditions where this equipment is to be used. Interacting with machines might present difficulties relative to the handiness of common interfacing devices, when wearing certain clothes, doing certain dirty jobs, or when they are used by people with accessibility needs. In the last decades a new set of input devices were made available, including 3D sensors, which allow machine interacting without the need of touching any device. This chapter presents two prototype solutions supported by one of this 3D sensors, the Leap Motion, to manage appliances and other devices in a building and for the picking and loading of vehicles in a warehouse. The first case is contextualized in the area of the IoT and load scheduling of appliances, as a decisive factor in reduction of the buildings' electrical costs. The second case is presented as a solution to integrate the distribution of fresh and frozen goods where workers use thick clothes/gloves to carry out their work.
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Arbib, Michael A. "An action-oriented perspective on space and affordances." In When Brains Meet Buildings. Oxford University Press, 2021. http://dx.doi.org/10.1093/med/9780190060954.003.0002.

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Architects design spaces that offer perceptual cues, affordances, for our various effectivities. Lina Bo Bardi’s São Paulo Museum demonstrates how praxic and contemplative actions are interleaved—space is effective and affective. Navigation often extends beyond wayfinding to support ongoing behavior. Scripts set out the general rules for a particular kind of behavior, and may suggest places that a building must provide. Cognitive maps support wayfinding. Other maps in the brain represent sensory or motor patterns of activity. Juhani Pallasmaa’s reflections on The Thinking Hand lead into a view of how the brain mediates that thinking, modeling hand–eye coordination at two levels. The first coordinates perceptual and motor schemas. The body schema is an adaptable collage of perceptual and motor skills. The second coordinates the ventral “what” pathway that can support planning of actions, and the dorsal “how” pathway that links affordance-related details to motor control. A complementary challenge is understanding how schemas in the head relate to social schemas. Finally, the chapter compares the cognitive challenges in designing a building and in developing a computational brain model of cognitive processes.
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Freeman, Margaret H. "Affect." In The Poem as Icon. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190080419.003.0006.

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Schemata acquire affective value through force dynamics at the deepest level of cognition. Affect is a transitive activity between the self as agonist and an “other” as antagonist that arises from sensory, motor, or emotive factors. In poetry, affect results primarily from a poem’s sonic and structural prosody to create the impression or “illusion” of virtual life. The affect respondents feel isn’t something static “in” the poem but a dynamic response to the poet’s intensions and motivations. Missing a poem’s affective tone can lead to misreading its emotive import and misevaluating the poet’s intension, as the discussion shows in a poem by Thomas Hardy. It also shows how the force dynamics of the FEAR schema in a Wallace Stevens poem creates an icon of danger confronting the self’s homeostasis. The chapter ends by summarizing the aspects of affective schemata that can lead to a theory of a model of affect in poetry and life.
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Conference papers on the topic "Leap motion sensor"

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Sharma, Jayash Kumar, Rajeev Gupta, and Vinay Kumar Pathak. "Numeral Gesture Recognition Using Leap Motion Sensor." In 2015 International Conference on Computational Intelligence and Communication Networks (CICN). IEEE, 2015. http://dx.doi.org/10.1109/cicn.2015.86.

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Elons, A. S., Menna Ahmed, Hwaidaa Shedid, and M. F. Tolba. "Arabic sign language recognition using leap motion sensor." In 2014 9th International Conference on Computer Engineering & Systems (ICCES). IEEE, 2014. http://dx.doi.org/10.1109/icces.2014.7030987.

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Chuan, Ching-Hua, Eric Regina, and Caroline Guardino. "American Sign Language Recognition Using Leap Motion Sensor." In 2014 13th International Conference on Machine Learning and Applications (ICMLA). IEEE, 2014. http://dx.doi.org/10.1109/icmla.2014.110.

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Mapari, Rajesh B., and Govind Kharat. "American Static Signs Recognition Using Leap Motion Sensor." In the Second International Conference. ACM Press, 2016. http://dx.doi.org/10.1145/2905055.2905125.

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Kaya, Mutlu, Burakhan Cubukcu, and Ugur Yuzgec. "Remote Vehicle Control with Leap Motion Touchless Sensor." In 2018 3rd International Conference on Computer Science and Engineering (UBMK). IEEE, 2018. http://dx.doi.org/10.1109/ubmk.2018.8566261.

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Mapari, Rajesh B., and Govind Kharat. "Real time human pose recognition using leap motion sensor." In 2015 IEEE International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN). IEEE, 2015. http://dx.doi.org/10.1109/icrcicn.2015.7434258.

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Chophuk, Ponlawat, Kanjana Pattanaworapan, and Kosin Chamnongthai. "Fist american sign language recognition using leap motion sensor." In 2018 International Workshop on Advanced Image Technology (IWAIT). IEEE, 2018. http://dx.doi.org/10.1109/iwait.2018.8369790.

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Caro, Luis, Emilio Villablanca, and Billy Peralta. "A Virtual Reality Application using Hand Motion Tracking with Leap Motion Sensor." In 2020 39th International Conference of the Chilean Computer Science Society (SCCC). IEEE, 2020. http://dx.doi.org/10.1109/sccc51225.2020.9281210.

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Saini, Rajkumar, Pradeep Kumar, Shweta Patidar, Partha Roy, and Marcus Liwicki. "Trilingual 3D Script Identification and Recognition using Leap Motion Sensor." In 2019 International Conference on Document Analysis and Recognition Workshops (ICDARW). IEEE, 2019. http://dx.doi.org/10.1109/icdarw.2019.40076.

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Dhanasree, K. S., K. K. Nisha, and R. Jayakrishnan. "Hospital Emergency Room Training Using Virtual Reality and Leap Motion Sensor." In 2018 Second International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2018. http://dx.doi.org/10.1109/iccons.2018.8662900.

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