1 resultado para Extended-spectrum
em Massachusetts Institute of Technology
Filtro por publicador
- Aberystwyth University Repository - Reino Unido (2)
- Adam Mickiewicz University Repository (1)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (1)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (1)
- Aquatic Commons (16)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (1)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (1)
- Aston University Research Archive (4)
- B-Digital - Universidade Fernando Pessoa - Portugal (3)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (4)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (6)
- Biblioteca Digital de Teses e Dissertações Eletrônicas da UERJ (5)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (20)
- Boston University Digital Common (3)
- Brock University, Canada (1)
- CaltechTHESIS (6)
- Cambridge University Engineering Department Publications Database (66)
- CentAUR: Central Archive University of Reading - UK (7)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (135)
- Coffee Science - Universidade Federal de Lavras (1)
- CORA - Cork Open Research Archive - University College Cork - Ireland (5)
- Deakin Research Online - Australia (3)
- DI-fusion - The institutional repository of Université Libre de Bruxelles (6)
- Digital Commons at Florida International University (1)
- DRUM (Digital Repository at the University of Maryland) (1)
- Duke University (2)
- eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry (4)
- Funes: Repositorio digital de documentos en Educación Matemática - Colombia (1)
- Greenwich Academic Literature Archive - UK (1)
- Helda - Digital Repository of University of Helsinki (20)
- Indian Institute of Science - Bangalore - Índia (177)
- Institutional Repository of Leibniz University Hannover (1)
- Instituto Politécnico de Bragança (1)
- Instituto Politécnico do Porto, Portugal (8)
- Massachusetts Institute of Technology (1)
- National Center for Biotechnology Information - NCBI (1)
- Plymouth Marine Science Electronic Archive (PlyMSEA) (3)
- Portal de Revistas Científicas Complutenses - Espanha (1)
- QSpace: Queen's University - Canada (1)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (223)
- Queensland University of Technology - ePrints Archive (161)
- Repositório Científico da Universidade de Évora - Portugal (1)
- Repositório do Centro Hospitalar de Lisboa Central, EPE - Centro Hospitalar de Lisboa Central, EPE, Portugal (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (21)
- 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)
- Universidad del Rosario, Colombia (10)
- Universidad Politécnica de Madrid (2)
- Universidade Complutense de Madrid (4)
- Universidade de Lisboa - Repositório Aberto (1)
- Universidade Federal do Pará (3)
- Université de Lausanne, Switzerland (3)
- Université de Montréal (1)
- Université de Montréal, Canada (3)
- University of Queensland eSpace - Australia (4)
- University of Washington (1)
- WestminsterResearch - UK (5)
Resumo:
We describe a new method for motion estimation and 3D reconstruction from stereo image sequences obtained by a stereo rig moving through a rigid world. We show that given two stereo pairs one can compute the motion of the stereo rig directly from the image derivatives (spatial and temporal). Correspondences are not required. One can then use the images from both pairs combined to compute a dense depth map. The motion estimates between stereo pairs enable us to combine depth maps from all the pairs in the sequence to form an extended scene reconstruction and we show results from a real image sequence. The motion computation is a linear least squares computation using all the pixels in the image. Areas with little or no contrast are implicitly weighted less so one does not have to explicitly apply a confidence measure.