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3D Object Reconstruction from Uncalibrated Images Using an Off-the-Shelf Camera

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Book cover Advances in Computational Vision and Medical Image Processing

Part of the book series: Computational Methods in Applied Sciences ((COMPUTMETHODS,volume 13))

Abstract

Three-dimensional (3D) objects reconstruction using just bi-dimensional (2D) images has been a major research topic in Computer Vision. However, it is still a hard problem to address, when automation, speed and precision are required and/or the objects have complex shapes or image properties. In this paper, we compare two Active Computer Vision methods frequently used for the 3D reconstruction of objects from image sequences, acquired with a single off-the-shelf CCD camera: Structure From Motion (SFM) and Generalized Voxel Coloring (GVC). SFM recovers the 3D shape of an object based on the relative motion involved, while VC is a volumetric method that uses photo-consistency measures to build the required 3D model. Both methods considered do not impose any kind of restrictions on the relative motion involved.

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Authors and Affiliations

  1. INEGI Instituto de Engenharia Mecânica e Gestão Industrial LOME Laboratório deóptica e Mecânica Experimental, FEUP Faculdade de Engenharia da Universidade do Porto, Portugal

    Teresa C. S. Azevedo

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  1. Teresa C. S. Azevedo
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  2. João Manuel R. S. Tavares
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  3. Mário A. P. Vaz
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  1. Institute of Mechanical Engineering and Industrial Management (INEGI), University of Porto (UP), Rua Dr. Roberto Frias, s/n, Porto, 4200-465, Portugal

    João Manuel R. S. Tavares (Faculty of Engineering (FEUP) & R. M. Natal Jorge (Faculty of Engineering (FEUP) (Faculty of Engineering (FEUP) &  (Faculty of Engineering (FEUP)

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Azevedo, T.C.S., Tavares, J.M.R.S., Vaz, M.A.P. (2009). 3D Object Reconstruction from Uncalibrated Images Using an Off-the-Shelf Camera. In: Tavares, J.M.R.S., Jorge, R.M.N. (eds) Advances in Computational Vision and Medical Image Processing. Computational Methods in Applied Sciences, vol 13. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9086-8_7

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  • DOI: https://doi.org/10.1007/978-1-4020-9086-8_7

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