• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 1
  • Tagged with
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Multi-resolu??o com f?vea m?vel para redu??o e abstra??o de dados em tempo real / Multi-resolu??o com f?vea m?vel para redu??o e abstra??o de dados em tempo real

Gomes, Rafael Beserra 07 August 2009 (has links)
Made available in DSpace on 2014-12-17T14:55:40Z (GMT). No. of bitstreams: 1 RafaelBG.pdf: 2393943 bytes, checksum: 45924e13c3c73c1eaaf09dcc478bd70e (MD5) Previous issue date: 2009-08-07 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / We propose a new approach to reduction and abstraction of visual information for robotics vision applications. Basically, we propose to use a multi-resolution representation in combination with a moving fovea for reducing the amount of information from an image. We introduce the mathematical formalization of the moving fovea approach and mapping functions that help to use this model. Two indexes (resolution and cost) are proposed that can be useful to choose the proposed model variables. With this new theoretical approach, it is possible to apply several filters, to calculate disparity and to obtain motion analysis in real time (less than 33ms to process an image pair at a notebook AMD Turion Dual Core 2GHz). As the main result, most of time, the moving fovea allows the robot not to perform physical motion of its robotics devices to keep a possible region of interest visible in both images. We validate the proposed model with experimental results / N?s propomos uma nova abordagem para reduzir e abstrair informa??es visuais para aplica??es de vis?o rob?tica. Basicamente, usamos uma representa??o emmulti-resolu??o em combina??o com uma f?vea m?vel para reduzir a quantidade de informa??es de uma imagem. Apresentamos a formaliza??o matem?tica do modelo em conjunto com fun??es de mapeamento que auxiliam na utiliza??o do modelo. Propomos dois ?ndices (resolu??o e custo) que visam auxiliar na escolha das vari?veis do modelo proposto. Com essa nova abordagem te?rica, ? poss?vel aplicar diversos filtros, calcular disparidade est?reo e obter an?lise de movimento em tempo real (menos de 33ms para processar um par de imagens em um notebook AMD Turion Dual Core 2GHz). Como principal resultado, na maior parte do tempo, a f?vea m?vel permite ao rob? n?o realizar movimenta??o f?sica de seus dispositivos rob?ticos para manter uma poss?vel regi?o de interesse vis?vel nas duas imagens. Validamos o modelo proposto com resultados experimentais

Page generated in 0.0488 seconds