76 resultados para Annotated Video Clips
Filtro por publicador
- JISC Information Environment Repository (2)
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- Brock University, Canada (16)
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- Cambridge University Engineering Department Publications Database (76)
- CentAUR: Central Archive University of Reading - UK (53)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (10)
- Cochin University of Science & Technology (CUSAT), India (5)
- Comissão Econômica para a América Latina e o Caribe (CEPAL) (5)
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- Duke University (6)
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- Fachlicher Dokumentenserver Paedagogik/Erziehungswissenschaften (1)
- Greenwich Academic Literature Archive - UK (8)
- Helda - Digital Repository of University of Helsinki (2)
- Indian Institute of Science - Bangalore - Índia (28)
- Instituto de Engenharia Nuclear, Brazil - Carpe dIEN (17)
- Instituto Politécnico do Porto, Portugal (3)
- Lume - Repositório Digital da Universidade Federal do Rio Grande do Sul (2)
- Massachusetts Institute of Technology (4)
- Memoria Académica - FaHCE, UNLP - Argentina (5)
- Ministerio de Cultura, Spain (27)
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- Portal de Revistas Científicas Complutenses - Espanha (2)
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- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (114)
- Queensland University of Technology - ePrints Archive (147)
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- Repositório digital da Fundação Getúlio Vargas - FGV (1)
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- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (7)
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- School of Medicine, Washington University, United States (7)
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- Universidad del Rosario, Colombia (3)
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- Universitat de Girona, Spain (2)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (1)
- Université de Lausanne, Switzerland (2)
- Université de Montréal (1)
- Université de Montréal, Canada (6)
- University of Queensland eSpace - Australia (2)
- University of Southampton, United Kingdom (44)
- University of Washington (1)
- WestminsterResearch - UK (4)
- Worcester Research and Publications - Worcester Research and Publications - UK (1)
Resumo:
We present a novel mixture of trees (MoT) graphical model for video segmentation. Each component in this mixture represents a tree structured temporal linkage between super-pixels from the first to the last frame of a video sequence. Our time-series model explicitly captures the uncertainty in temporal linkage between adjacent frames which improves segmentation accuracy. We provide a variational inference scheme for this model to estimate super-pixel labels and their confidences in nearly realtime. The efficacy of our approach is demonstrated via quantitative comparisons on the challenging SegTrack joint segmentation and tracking dataset [23].