16 resultados para STELLAR ROTATION
Filtro por publicador
- Aberdeen University (1)
- Academic Archive On-line (Stockholm University; Sweden) (1)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (14)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (7)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (2)
- Archimer: Archive de l'Institut francais de recherche pour l'exploitation de la mer (1)
- Archive of European Integration (1)
- Aston University Research Archive (17)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (27)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (184)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (51)
- Brock University, Canada (3)
- Bucknell University Digital Commons - Pensilvania - USA (2)
- Bulgarian Digital Mathematics Library at IMI-BAS (2)
- CentAUR: Central Archive University of Reading - UK (27)
- CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal (1)
- Cochin University of Science & Technology (CUSAT), India (1)
- Coffee Science - Universidade Federal de Lavras (1)
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- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (22)
- Düsseldorfer Dokumenten- und Publikationsservice (1)
- Gallica, Bibliotheque Numerique - Bibliothèque nationale de France (French National Library) (BnF), France (2)
- Illinois Digital Environment for Access to Learning and Scholarship Repository (1)
- Instituto Politécnico do Porto, Portugal (30)
- Iowa Publications Online (IPO) - State Library, State of Iowa (Iowa), United States (3)
- Massachusetts Institute of Technology (3)
- National Center for Biotechnology Information - NCBI (7)
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- QSpace: Queen's University - Canada (1)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (8)
- Repositório Alice (Acesso Livre à Informação Científica da Embrapa / Repository Open Access to Scientific Information from Embrapa) (2)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (11)
- Repositório da Produção Científica e Intelectual da Unicamp (14)
- Repositório do Centro Hospitalar de Lisboa Central, EPE - Centro Hospitalar de Lisboa Central, EPE, Portugal (2)
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- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (33)
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- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (16)
- School of Medicine, Washington University, United States (1)
- Scielo Saúde Pública - SP (73)
- Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom (1)
- Universidad de Alicante (10)
- Universidad Politécnica de Madrid (13)
- Universidade Complutense de Madrid (16)
- Universidade do Minho (18)
- Universidade dos Açores - Portugal (3)
- Universidade Federal do Pará (1)
- Universidade Federal do Rio Grande do Norte (UFRN) (23)
- Universidade Técnica de Lisboa (1)
- Universitat de Girona, Spain (1)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (6)
- Université de Lausanne, Switzerland (104)
- Université de Montréal (2)
- Université de Montréal, Canada (9)
- University of Canberra Research Repository - Australia (1)
- University of Connecticut - USA (2)
- University of Michigan (13)
- University of Queensland eSpace - Australia (96)
- University of Washington (1)
- Worcester Research and Publications - Worcester Research and Publications - UK (1)
Resumo:
Human-Computer Interaction have been one of the main focus of the technological community, specially the Natural User Interfaces (NUI) field of research as, since the launch of the Kinect Sensor, the goal to achieve fully natural interfaces just got a lot closer to reality. Taking advantage of this conditions the following research work proposes to compute the hand skeleton in order to recognize Sign Language Shapes. The proposed solution uses the Kinect Sensor to achieve a good segmentation and image analysis algorithms to extend the skeleton from the extraction of high-level features. In order to recognize complex hand shapes the current research work proposes the redefinition of the hand contour making it immutable to translation, rotation and scaling operations, and a set of tools to achieve a good recognition. The validation of the proposed solution extended the Kinects Software Development Kit to allow the developer to access the new set of inferred points and created a template-matching based platform that uses the contour to define the hand shape, this prototype was tested in a set of predefined conditions and showed to have a good success ration and has proven to be eligible for real-time scenarios.