76 resultados para Rear-View Mirrors.
Filtro por publicador
- JISC Information Environment Repository (1)
- Aberystwyth University Repository - Reino Unido (2)
- Adam Mickiewicz University Repository (1)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (1)
- Andina Digital - Repositorio UASB-Digital - Universidade Andina Simón Bolívar (1)
- Applied Math and Science Education Repository - Washington - USA (1)
- Aquatic Commons (17)
- Archive of European Integration (18)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (7)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (6)
- Biblioteca Digital de la Universidad Católica Argentina (1)
- Biblioteca Digital de Teses e Dissertações Eletrônicas da UERJ (3)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (3)
- Boston University Digital Common (4)
- Brock University, Canada (24)
- CaltechTHESIS (4)
- Cambridge University Engineering Department Publications Database (76)
- CentAUR: Central Archive University of Reading - UK (103)
- Center for Jewish History Digital Collections (54)
- Chapman University Digital Commons - CA - USA (15)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (25)
- Cochin University of Science & Technology (CUSAT), India (2)
- Comissão Econômica para a América Latina e o Caribe (CEPAL) (12)
- CORA - Cork Open Research Archive - University College Cork - Ireland (2)
- CUNY Academic Works (8)
- Dalarna University College Electronic Archive (1)
- Department of Computer Science E-Repository - King's College London, Strand, London (1)
- DI-fusion - The institutional repository of Université Libre de Bruxelles (2)
- Digital Archives@Colby (8)
- Digital Commons at Florida International University (1)
- DRUM (Digital Repository at the University of Maryland) (1)
- Duke University (2)
- Greenwich Academic Literature Archive - UK (2)
- Helda - Digital Repository of University of Helsinki (13)
- Indian Institute of Science - Bangalore - Índia (37)
- Instituto Politécnico do Porto, Portugal (2)
- Lume - Repositório Digital da Universidade Federal do Rio Grande do Sul (2)
- Massachusetts Institute of Technology (8)
- Ministerio de Cultura, Spain (7)
- Plymouth Marine Science Electronic Archive (PlyMSEA) (10)
- Portal de Revistas Científicas Complutenses - Espanha (3)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (102)
- Queensland University of Technology - ePrints Archive (104)
- ReCiL - Repositório Científico Lusófona - Grupo Lusófona, Portugal (1)
- Repositório Científico da Universidade de Évora - Portugal (1)
- Repositório digital da Fundação Getúlio Vargas - FGV (6)
- Repositório Digital da Universidade Municipal de São Caetano do Sul - USCS (1)
- REPOSITORIO DIGITAL IMARPE - INSTITUTO DEL MAR DEL PERÚ, Peru (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (30)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (2)
- SAPIENTIA - Universidade do Algarve - Portugal (1)
- School of Medicine, Washington University, United States (1)
- Universidad Autónoma de Nuevo León, Mexico (6)
- Universidad del Rosario, Colombia (3)
- Universidade Federal do Rio Grande do Norte (UFRN) (2)
- Universitat de Girona, Spain (2)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (8)
- Université de Lausanne, Switzerland (2)
- Université de Montréal, Canada (9)
- University of Michigan (98)
- University of Queensland eSpace - Australia (6)
- University of Southampton, United Kingdom (4)
- WestminsterResearch - UK (3)
Resumo:
This paper describes an interactive system for quickly modelling 3D body shapes from a single image. It provides the user with a convenient way to obtain their 3D body shapes so as to try on virtual garments online. For the ease of use, we first introduce a novel interface for users to conveniently extract anthropometric measurements from a single photo, while using readily available scene cues for automatic image rectification. Then, we propose a unified probabilistic framework using Gaussian processes, which predict the body parameters from input measurements while correcting the aspect ratio ambiguity resulting from photo rectification. Extensive experiments and user studies have supported the efficacy of our system. This system is now being exploited commercially online1. © 2011. The copyright of this document resides with its authors.