46 resultados para ARTES DO VIDEO
Filtro por publicador
- JISC Information Environment Repository (1)
- Abertay Research Collections - Abertay University’s repository (1)
- Aberystwyth University Repository - Reino Unido (1)
- Adam Mickiewicz University Repository (1)
- Andina Digital - Repositorio UASB-Digital - Universidade Andina Simón Bolívar (11)
- Aquatic Commons (13)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (22)
- Biblioteca Digital da Câmara dos Deputados (1)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (3)
- Biblioteca Digital de la Universidad Católica Argentina (1)
- Biblioteca Digital de Teses e Dissertações Eletrônicas da UERJ (18)
- Boston University Digital Common (12)
- Brock University, Canada (7)
- Cámara de Comercio de Bogotá, Colombia (4)
- Cambridge University Engineering Department Publications Database (76)
- CentAUR: Central Archive University of Reading - UK (46)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (8)
- CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal (2)
- Cochin University of Science & Technology (CUSAT), India (5)
- CORA - Cork Open Research Archive - University College Cork - Ireland (2)
- CUNY Academic Works (2)
- Dalarna University College Electronic Archive (11)
- Deakin Research Online - Australia (65)
- Department of Computer Science E-Repository - King's College London, Strand, London (2)
- Diposit Digital de la UB - Universidade de Barcelona (1)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (1)
- DRUM (Digital Repository at the University of Maryland) (1)
- Duke University (2)
- Gallica, Bibliotheque Numerique - Bibliothèque nationale de France (French National Library) (BnF), France (2)
- Greenwich Academic Literature Archive - UK (8)
- Helda - Digital Repository of University of Helsinki (2)
- Indian Institute of Science - Bangalore - Índia (24)
- Instituto de Engenharia Nuclear, Brazil - Carpe dIEN (17)
- Instituto Politécnico do Porto, Portugal (3)
- Massachusetts Institute of Technology (4)
- Ministerio de Cultura, Spain (202)
- Portal de Revistas Científicas Complutenses - Espanha (8)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (101)
- Queensland University of Technology - ePrints Archive (125)
- ReCiL - Repositório Científico Lusófona - Grupo Lusófona, Portugal (3)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (10)
- REPOSITORIO DIGITAL IMARPE - INSTITUTO DEL MAR DEL PERÚ, Peru (11)
- Repositório Institucional da Universidade de Aveiro - Portugal (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (3)
- Research Open Access Repository of the University of East London. (2)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (15)
- SAPIENTIA - Universidade do Algarve - Portugal (7)
- School of Medicine, Washington University, United States (7)
- SerWisS - Server für Wissenschaftliche Schriften der Fachhochschule Hannover (1)
- Universidad Autónoma de Nuevo León, Mexico (25)
- Universidad del Rosario, Colombia (22)
- Universidade de Lisboa - Repositório Aberto (9)
- Universidade Federal do Rio Grande do Norte (UFRN) (1)
- Universitat de Girona, Spain (12)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (1)
- Université de Lausanne, Switzerland (2)
- Université de Montréal, Canada (3)
- University of Southampton, United Kingdom (37)
- University of Washington (1)
- WestminsterResearch - UK (3)
Resumo:
In this paper we present a novel approach to detect people meeting. The proposed approach works by translating people behaviour from trajectory information into semantic terms. Having available a semantic model of the meeting behaviour, the event detection is performed in the semantic domain. The model is learnt employing a soft-computing clustering algorithm that combines trajectory information and motion semantic terms. A stable representation can be obtained from a series of examples. Results obtained on a series of videos with different types of meeting situations show that the proposed approach can learn a generic model that can effectively be applied on the behaviour recognition of meeting situations.